Pith. sign in

Paper Citation Record · LEDGER

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation

As of 13 August 2026, this Paper Citation Record lists 89 of 89 outbound references and 0 inbound Pith citation observations for arXiv:2411.15763.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.15763 v1

Coverage vector

measured 89 of 89 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:58:53.834808Z

measured 89 of 89 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

89 of 89 outbound references displayed

  • verified exact5
  • verified fuzzy53
  • unresolved31
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b584ac5-93ab-4be2-b189-e7d168f5be60 · outbound

This paper cites Annotation-efficient deep learning for automatic medical image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Annotation-efficient deep learning for automatic medical image segmentation

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.505733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.505733Z digest=sha256:7e1462b2a28b9112095f4deddddda18cd4a24b03c7eab2cf992d1c4d3f3206ab

Observation db00c723-882e-4eb5-9e2b-4e22fa116409 · outbound

This paper cites Weakly-supervised convolu- tional neural networks for vessel segmentation in cerebral angiography.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Weakly-supervised convolu- tional neural networks for vessel segmentation in cerebral angiography

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.510241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.510241Z digest=sha256:c1bf23ce9e93fb3919932f375d434d84f636178cc87d938952c2b55914ab5472

Observation 0e57ef8b-b5ac-4a27-bac4-37cc18d31c2c · outbound

This paper cites 3d u-net: learning dense volumetric segmentation from sparse annotation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation 3d u-net: learning dense volumetric segmentation from sparse annotation

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.514400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.514400Z digest=sha256:52f7a65a701ad8822b045a9a231151bd60f038f2aa9eaac546adb967e567b34b

Observation 7a0d2b7f-3556-428d-9925-49f955a4b2f0 · outbound

This paper cites Auto-annotated deep segmentation for surface defect detection.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Auto-annotated deep segmentation for surface defect detection

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.518388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.518388Z digest=sha256:e440a57a592928fca64350d0e04845b28f573e580aae28d3c8fce4048d3a3e10

Observation 4becb7f8-f308-44e8-a35c-95451a2d4b24 · outbound

This paper cites Less Is More: A Comparison of Active Learning Strategies for 3D Medical Image Segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Less Is More: A Comparison of Active Learning Strategies for 3D Medical Image Segmentation

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-08-12T13:58:54.046978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.522758Z digest=sha256:52ee62e5a5a67b9c2938c5b70b3a5455cf755f9990276be52dec371f25138f3b

Observation 56a5bed7-121e-4e77-b636-9a20ec263763 · outbound

This paper cites Colossal: A benchmark for cold-start active learning for 3d medical image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Colossal: A benchmark for cold-start active learning for 3d medical image segmentation

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.527273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.527273Z digest=sha256:b94cac889063834ad1f37ef78171980ba00e506d546fd2b9a9a357f9e0e22803

Observation 1ab9cb74-7b91-407b-83d7-3718a034c0de · outbound

This paper cites Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Universal Weakly Supervised Segmentation by Pixel-to-Segment Contrastive Learning

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.531226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.531226Z digest=sha256:0722af914846abe057d2ebe24ec6bf7282999d361c002c5b868579f008d62989

Observation 8e0b0785-737c-49dc-9e65-a3c2468d9668 · outbound

This paper cites Scribble-based hierarchical weakly supervised learning for brain tumor segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Scribble-based hierarchical weakly supervised learning for brain tumor segmentation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.535379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.535379Z digest=sha256:84a27f53c5fd386a7631564df1adbdd40876e4fc6f276409a3ad137c81ba9c54

Observation 64e836e2-b6a9-4b9c-8841-e11f3e20a617 · outbound

This paper cites Scribble2d5: Weakly-supervised volumetric image segmentation via scribble annotations.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Scribble2d5: Weakly-supervised volumetric image segmentation via scribble annotations

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.539094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.539094Z digest=sha256:5c8de7d25eb3b5dacae41592209a73c1cef26fd1679147356c7614f90776d72d

Observation c8e89811-5161-45e1-90c1-f86b79ef11ef · outbound

This paper cites Box2mask: Weakly supervised 3d semantic instance segmentation using bounding boxes.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Box2mask: Weakly supervised 3d semantic instance segmentation using bounding boxes

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.542735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.542735Z digest=sha256:957b002399f0be4a9e5e61d3ec56292f0821c89061d4201c9a3def795a6f0c03

Observation b54deaa5-7925-42dc-9759-2537e2edf7fc · outbound

This paper cites Weakly supervised segmentation with point annotations for histopathology images via contrast-based variational model.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Weakly supervised segmentation with point annotations for histopathology images via contrast-based variational model

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.546687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.546687Z digest=sha256:1e4b179933db3ab248e0a476a3e604af29e988f321a68bfc96aee66bc8a7f219

Observation 0eb8725b-63fe-42b8-9373-c29583398088 · outbound

This paper cites Affinity attention graph neural network for weakly supervised semantic segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Affinity attention graph neural network for weakly supervised semantic segmentation

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.715430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.550451Z digest=sha256:2ff22a026e62dbfee88ec96fb240e812e94325d2b627114345834a26775c4085

Observation e4542ca9-e1a5-4604-a3c4-0c3985f51c3d · outbound

This paper cites Comparative evaluation of conventional and deep learning methods for semi-automated segmentation of pulmonary nodules on ct.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Comparative evaluation of conventional and deep learning methods for semi-automated segmentation of pulmonary nodules on ct

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.705705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.554219Z digest=sha256:d59fe4571193b5f6fb77d197e0b6f3f6ee543e1f4062803680106deb31ce1212

Observation 33ab2235-7dc6-43e4-bc70-e1e5a4659c55 · outbound

This paper cites Semi-automated and interactive segmentation of contrast-enhancing masses on breast dce-mri using spatial fuzzy clustering.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Semi-automated and interactive segmentation of contrast-enhancing masses on breast dce-mri using spatial fuzzy clustering

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.695761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.557984Z digest=sha256:6a9c120a777057f4f3ce001ceeb057c1527caccab6762641fa4201c289b9d683

Observation 40e49b5e-b573-4eea-bd60-e8c2eb2f0fdd · outbound

This paper cites Interactive segmentation of medical images through fully convolutional neural networks.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Interactive segmentation of medical images through fully convolutional neural networks

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.561890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.561890Z digest=sha256:b0822128e46cb5f1e3a941a1e475bd72437ddcf4224788eab526c8d1cff11b43

Observation 8c3a4c33-04d4-4955-b0fb-2e824fd93c44 · outbound

This paper cites An unsupervised semi-automated pulmonary nodule segmentation method based on enhanced region growing.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation An unsupervised semi-automated pulmonary nodule segmentation method based on enhanced region growing

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.685079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.565324Z digest=sha256:86ae45ba7fcaeae490c271386f8cca5f8fce2055fa5e4e982edc34cd8688be9b

Observation aac59e18-89e5-4aa6-b691-a4c7d8f0be45 · outbound

This paper cites Learning to segment from scrib- bles using multi-scale adversarial attention gates.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Learning to segment from scrib- bles using multi-scale adversarial attention gates

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.673978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.568407Z digest=sha256:15ea179b5cb04d6c4a5e3a4dbe74ba24f0b58e7c1907a6f0974d9167bb9826ac

Observation 421313b2-e521-41d5-b956-27d7ec3c19c7 · outbound

This paper cites Scribble-supervised medical image segmentation via dual-branch network and dynamically mixed pseudo labels supervision.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Scribble-supervised medical image segmentation via dual-branch network and dynamically mixed pseudo labels supervision

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.662166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.571659Z digest=sha256:fc3c823936159b343b94f89167240b0e193d347157a02996538f41a47a778c92

Observation ffbb600b-b4a2-4a25-a8a5-e295ba781e7a · outbound

This paper cites Transformer based multiple instance learning for weakly supervised histopathology image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Transformer based multiple instance learning for weakly supervised histopathology image segmentation

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.649922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.574775Z digest=sha256:b7fce34740bc6a8de057f28a1cfc4256d1697d232f4a225dea95b45916491dc5

Observation 1fa8b51c-bd2c-4193-a2d5-f7fc12fa94bd · outbound

This paper cites Multi-scale feature similarity-based weakly supervised lymphoma segmentation in pet/ct images.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Multi-scale feature similarity-based weakly supervised lymphoma segmentation in pet/ct images

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.637568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.578334Z digest=sha256:af1ef7bf4989fd7af0ad93521d451902b87eb577250e7725a16fe37499e9b40c

Observation ad240444-591c-4780-ac4e-a10ce72b9ed1 · outbound

This paper cites Max pooling with vision transformers reconciles class and shape in weakly supervised semantic segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Max pooling with vision transformers reconciles class and shape in weakly supervised semantic segmentation

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.625999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.581992Z digest=sha256:a9e31209a195f4c2288af9df1abe820ca9c0df5a30a5ba77c57d190969f6f6ca

Observation 782965bb-7fa6-44e5-a085-aa763f3ae49b · outbound

This paper cites Boosting active learning via improving test performance.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Boosting active learning via improving test performance

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.614102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.585457Z digest=sha256:ceb3a2f7386af6cc9cfcfabb3c1d927dc3b0ab719a3c2f63caa7f5fc326f83c2

Observation 55402a3d-33e9-469d-a907-706f043fa061 · outbound

This paper cites Deep bayesian active learning with image data.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep bayesian active learning with image data

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.602416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.589120Z digest=sha256:ed45e49f282bfb50e0d382a824ebbe29aa21fd1c82588b1d04abbf2bbb1fc3a8

Observation 4b34e1e3-6c52-413c-a65a-ac0a7c4dbae5 · outbound

This paper cites Deep Bayesian Active Learning, A Brief Survey on Recent Advances.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep Bayesian Active Learning, A Brief Survey on Recent Advances

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.592517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.592517Z digest=sha256:acf00e9dc6dec9815dec660989233490ca947d51bea407ce6fa0aa6dee0fdb20

Observation 9391bbda-281d-4b4e-8a36-001d894b2361 · outbound

This paper cites Batchbald: Efficient and diverse batch acquisition for deep bayesian active learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Batchbald: Efficient and diverse batch acquisition for deep bayesian active learning

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.596548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.596548Z digest=sha256:b1bc0c28f4e4e65e04cbeb725413a7270b413fc733bda8b14678871c2af36c74

Observation 37be0db0-9dd6-4da4-8282-59baaca0b08b · outbound

This paper cites Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.600187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.600187Z digest=sha256:10915ae71dfdf4a3f9c28a73fd3871346a84b93e965ebe4f7726f23b6988698c

Observation 1650041b-3efc-4ad3-9c6e-6fdecdc12535 · outbound

This paper cites The power of ensembles for active learning in image classification.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation The power of ensembles for active learning in image classification

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.585499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.604283Z digest=sha256:760f38e2a6ae753db9c25697bce43ba792c0a67fa8e079ca00c51ec579db138e

Observation c47d6a11-5dc4-4498-a669-bf2b4c7cce92 · outbound

This paper cites Large-Scale Visual Active Learning with Deep Probabilistic Ensembles.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Large-Scale Visual Active Learning with Deep Probabilistic Ensembles

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.607952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.607952Z digest=sha256:89f75a5709b8c36f3c7f90d4f3b3e1751317bf34a195058fd843f95cd64da0e4

Observation dc3d0450-cd1e-48b3-9eb7-981dd5cb5dc9 · outbound

This paper cites Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep Ensemble Bayesian Active Learning : Addressing the Mode Collapse issue in Monte Carlo dropout via Ensembles

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.611933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.611933Z digest=sha256:000ab726df6fadaf8928e5d4b481e5f702bda9cd7aa6d43330bc10cd0c936430

Observation 547420b3-3c2a-4b89-8863-3d37d07416ac · outbound

This paper cites A simple yet powerful deep active learning with snapshots ensembles.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation A simple yet powerful deep active learning with snapshots ensembles

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.575984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.615868Z digest=sha256:68c895b7a3f667cca7b51a295fe6bcacfdd4f98df87bcea1127d867534d02bf2

Observation 1ade6a46-d9ff-4dc3-b4d5-6fc8458f654b · outbound

This paper cites Active learning for medical image segmentation with stochastic batches.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Active learning for medical image segmentation with stochastic batches

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-12T13:58:53.970742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.619695Z digest=sha256:ef09d6493f27bf1b98eb1e5b2a48d33698586191769891dd308c0dab91150ec6

Observation 8dfd2a5f-b105-4139-8da1-eb42353a2f19 · outbound

This paper cites One-bit active query with contrastive pairs.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation One-bit active query with contrastive pairs

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.565108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.624272Z digest=sha256:dff1653d51230358532c4bd01dc0fea7a7c4d4444d4cc79a6328b420198993b5

Observation 324f529f-fc29-4269-8cab-68333993e8f3 · outbound

This paper cites Active Learning by Acquiring Contrastive Examples.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Active Learning by Acquiring Contrastive Examples

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.627864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.627864Z digest=sha256:38fc430d671949347bfe5b02235b872c2c83ad1a6496a8403624db4d9f1a0868

Observation 5ec6ce84-e666-4cf4-a93c-a943a2572f76 · outbound

This paper cites When Contrastive Learning Meets Active Learning: A Novel Graph Active Learning Paradigm with Self-Supervision.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation When Contrastive Learning Meets Active Learning: A Novel Graph Active Learning Paradigm with Self-Supervision

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-08-12T13:58:53.946966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.631755Z digest=sha256:c83cdd303adf5504d8c5236625553640aa998483ed7e4db6cfc7b0ef2448a3a9

Observation 2699ab05-68b9-4e8b-8880-e862c0d27677 · outbound

This paper cites Deep Active Learning with Contrastive Learning Under Realistic Data Pool Assumptions.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep Active Learning with Contrastive Learning Under Realistic Data Pool Assumptions

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-12T13:58:53.933227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.635932Z digest=sha256:a89692affa93264eb17121240fb0ce0bf7d99fef937337d368f1e9e2af73acbd

Observation df930e20-1c48-4326-8d1d-11f4f0ed349b · outbound

This paper cites Hyperbolic Active Learning for Semantic Segmentation under Domain Shift.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Hyperbolic Active Learning for Semantic Segmentation under Domain Shift

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.639542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.639542Z digest=sha256:80263a3955cf9f6e5aed4ecc8d680a47728eaf8e38579e07102e46d4713c9a6c

Observation 12f49777-9fac-43b2-9f36-d6f988668031 · outbound

This paper cites Active Learning for Convolutional Neural Networks: A Core-Set Approach.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Active Learning for Convolutional Neural Networks: A Core-Set Approach

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.643184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.643184Z digest=sha256:9bc3e71040ea789ebde55a0427840fc79b5853b8309e9ef5c1fdf73bcd86ef4e

Observation 4757a74f-25f5-4051-a24c-89e67aef096a · outbound

This paper cites Sequential graph convolutional network for active learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Sequential graph convolutional network for active learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.552651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.646638Z digest=sha256:920be0a30a88915e4e5577c11fac81166d786b3bd7e512b67f1e80eb3d57669f

Observation f3cedfd5-2baf-48a7-be49-e39527b37207 · outbound

This paper cites Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.649602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.649602Z digest=sha256:f3e6cba33368dcd3c38f0fb80e53c8a71bcf96cf67fea46e9d4e297050ae5bbd

Observation 0c7891b3-f3bb-4e2d-9784-77f40fb7052d · outbound

This paper cites Variational adversarial active learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Variational adversarial active learning

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.541789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.653350Z digest=sha256:6f148a53bf50ba86e58024b89212f28d89a6c39f8ddf5b2000a2d17e0fe19b17

Observation 038d4da8-0630-42cd-893d-50287c082da7 · outbound

This paper cites Task-aware variational adversarial active learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Task-aware variational adversarial active learning

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.529483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.656861Z digest=sha256:102103326d869a7facfe3fa4d1064e8a07a83179b3b401b48e6b6525d9fd6761

Observation 3454eca2-b506-4823-9412-68f7ca62a25c · outbound

This paper cites Towards robust and reproducible active learning using neural networks.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Towards robust and reproducible active learning using neural networks

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.517307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.660583Z digest=sha256:62f11ae0ed4a49e41587fc349705578964cbd69903038220e147ccae66cefcbb

Observation 78cc702f-e323-4f82-af24-19c43a6c039e · outbound

This paper cites Improved deep metric learning with multi-class n-pair loss objective.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Improved deep metric learning with multi-class n-pair loss objective

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.664499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.664499Z digest=sha256:b6be4d58558b897b052d71f56de4d50cdf1114e779942caefa20adaf029d56be

Observation 73a08c38-bc98-48ac-b210-3b7897ead11f · outbound

This paper cites Contrastive learning of global and local features for medical image segmentation with limited annotations.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Contrastive learning of global and local features for medical image segmentation with limited annotations

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.498136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.667988Z digest=sha256:a6dd3b994a69a74c9266073c8c7c02fbfc5bc369f3b18787ef4c406356e74704

Observation ef74e5cf-00d8-4808-ad66-dcf92739e863 · outbound

This paper cites 3d self-supervised methods for medical imaging.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation 3d self-supervised methods for medical imaging

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.486090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.671531Z digest=sha256:c934f41e1159eda89b8af51a3f219a40d229b7fc3c30b9761ff9113166666ad0

Observation 63fdb470-8e6a-4b11-8661-d1d4a50989bd · outbound

This paper cites Are binary annotations sufficient? video moment retrieval via hier- archical uncertainty-based active learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Are binary annotations sufficient? video moment retrieval via hier- archical uncertainty-based active learning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.474520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.676125Z digest=sha256:7c3237197dea0179ffc84ac8a2e65c06d7a256a3a70d4a98ba5db75fc3f06f81

Observation 489a1d8f-10e3-49d8-9ead-ff4350a56e07 · outbound

This paper cites Active learning for domain adaptation: An energy-based approach.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Active learning for domain adaptation: An energy-based approach

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.464087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.680886Z digest=sha256:7b29623251e67c3f4645616a19fa861b608f2dedada776197a88cdb16a0f37ea

Observation 9d3eb0ca-b3c1-4bbc-9c17-5bf5c4f9ef3a · outbound

This paper cites Extending contrastive learning to unsupervised coreset selection.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Extending contrastive learning to unsupervised coreset selection

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.453967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.684610Z digest=sha256:3fb23ebca8a7913e8864c918060318232d88769f961498bff554f41219d0b978

Observation 9f25df4d-cfab-446b-9668-8057bbea9c1d · outbound

This paper cites One-shot active learning for image segmentation via contrastive learning and diversity-based sampling.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation One-shot active learning for image segmentation via contrastive learning and diversity-based sampling

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.443022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.688223Z digest=sha256:aa8f42cacd6f1544e80dab58d2d2c940baa7de01d8a2c7727c5ea238c6d3429e

Observation 99b2c045-7ed6-4c11-9ef4-943a4eb4ff5c · outbound

This paper cites Deep metric learning for computer vision: A brief overview.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep metric learning for computer vision: A brief overview

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.429712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.691906Z digest=sha256:d39e039f295045dc6b50fd5b20c14ddf9d287ffe2815ff0316dc4e966672ebcb

Observation b8ab2af1-d88e-4e85-bd59-19a38124ca8c · outbound

This paper cites Facenet: A unified embedding for face recognition and clustering.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Facenet: A unified embedding for face recognition and clustering

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.695635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.695635Z digest=sha256:ffdbabb86d6b06fa83f654ff4ae6da331d9f2aa8c67334c8a8069ba82ef78f8e

Observation c5c1d086-f8a6-43b9-98cd-1efac634996c · outbound

This paper cites A discriminative feature learning approach for deep face recognition.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation A discriminative feature learning approach for deep face recognition

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.409367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.699061Z digest=sha256:e3b9de50db69538edc74cd55d2f45e352f8b1bd7924d5406fa59058b554e5ae1

Observation 7bbaa1f8-447d-4715-9005-a2e9aab942d2 · outbound

This paper cites Arcface: Additive angular margin loss for deep face recognition.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Arcface: Additive angular margin loss for deep face recognition

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.398359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.702593Z digest=sha256:4105dde18a6f7fec2945c9a4a94460e6da6c0d6188182688265d044a27a6a02f

Observation 6aa23f85-6fb1-4bf4-8f08-84388b584203 · outbound

This paper cites Sub-center arcface: Boosting face recognition by large-scale noisy web faces.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Sub-center arcface: Boosting face recognition by large-scale noisy web faces

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.387212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.706098Z digest=sha256:932e4e8acee42a45e604c15d0bd7d17b23539038005095b40393b8f72e1304ee

Observation df420792-b41c-4ec0-a744-7c3935bcbd9f · outbound

This paper cites No fuss distance metric learning using proxies.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation No fuss distance metric learning using proxies

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.376458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.710093Z digest=sha256:d037bca27732ff0884960b57b823f3b3d3ca272f6e9619a0ad5b5498f9d8e82c

Observation c95a5596-6de7-4e57-8c47-9ec8291623ef · outbound

This paper cites Proxynca++: Revisiting and revitalizing proxy neighborhood component analysis.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Proxynca++: Revisiting and revitalizing proxy neighborhood component analysis

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.365401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.713345Z digest=sha256:136521b7272378e92a06218890064af2929dc1007205ec22c2c7bf82fc98e2ed

Observation 29940290-0f72-4a11-9377-ddd8fac68f83 · outbound

This paper cites Napreg: nouns as proxies regularization for semantically aware cross-modal embeddings.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Napreg: nouns as proxies regularization for semantically aware cross-modal embeddings

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.353843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.716860Z digest=sha256:ad3854585ce44c468f8bff71d11cbfe3f3a586f92eb80909ad75d8189b31705f

Observation 688d206e-a501-4725-bf71-0c9e813ba345 · outbound

This paper cites Integrating language guidance into vision- based deep metric learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Integrating language guidance into vision- based deep metric learning

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.342742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.719974Z digest=sha256:26ac2932db7888f00237c3a48f4dae4c08d5fd5b5ca54fcc711f6c0d0fdff330

Observation b288644d-4514-470f-9172-ad4c8705370d · outbound

This paper cites Ensemble deep manifold similarity learning using hard proxies.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Ensemble deep manifold similarity learning using hard proxies

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.331285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.724926Z digest=sha256:5a0c7e6a48142cc0481e749754ffed322a787cd8a38c638ffa39a827866bfda7

Observation 2a88b370-33f9-495c-84a1-f32c0779e8f7 · outbound

This paper cites Deep metric learning with bier: Boosting independent embeddings robustly.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep metric learning with bier: Boosting independent embeddings robustly

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.319460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.728403Z digest=sha256:ee20ba1068f755bde11f8421b00290ba74da63d051e23aca1255cb05a58ccea8

Observation c1a1d3ff-980b-42e5-96fe-5f4078a2d9ee · outbound

This paper cites Softtriple loss: Deep metric learning without triplet sampling.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Softtriple loss: Deep metric learning without triplet sampling

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.307963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.732450Z digest=sha256:cb7d79a7da01522b86847b1a3e33482c649d360d333daca6305fa7202bffec0c

Observation 6251cf03-c96b-4384-ae3d-aae2cee89759 · outbound

This paper cites Mic: Mining interclass characteristics for improved metric learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Mic: Mining interclass characteristics for improved metric learning

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.296481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.736563Z digest=sha256:4a04a83c2447768a9a87cd2abedabcc76c19ce0300d0266e10826525d9807340

Observation 9c04bfa2-42ed-4845-8841-f06685c2bbed · outbound

This paper cites Deep randomized ensembles for metric learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep randomized ensembles for metric learning

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.284042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.740611Z digest=sha256:6180a6323b1ebc0cfde2653bc7a2d721183f319d2c21dbba9278684ef63b422f

Observation 5e0d3040-d483-4402-b62f-dbfcbdb6c440 · outbound

This paper cites Deep factorized metric learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep factorized metric learning

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.272118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.744490Z digest=sha256:247faff78cd52939d41f291ed24c14f2bb8a679460deea15e9a9f70bbcb8ac4f

Observation c46cf85d-5deb-4457-aeb5-6825d06fcdc4 · outbound

This paper cites Deep semi-supervised metric learning with mixed label propagation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep semi-supervised metric learning with mixed label propagation

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.260376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.748282Z digest=sha256:8259a6c481a4134d7f9e833a274932dc2d79235eae2c34d15a9f7a97b90bbb89

Observation a5b42630-f910-4602-9fc7-1ef277908cb7 · outbound

This paper cites Semi-supervised metric learning: A deep resurrection.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Semi-supervised metric learning: A deep resurrection

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.249004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.751944Z digest=sha256:a65ee08a24c8b3811c96499054bad276f06f6529e6cbc4a119260f5227a5fa8c

Observation 28a15147-c26a-4da6-90b1-53dec733bec8 · outbound

This paper cites Self-supervised learning for medical image analysis using image context restoration.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Self-supervised learning for medical image analysis using image context restoration

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.236570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.756232Z digest=sha256:2696e14eedcb3809533f752c6e15da79d04c2d2e1020d719a7bfd39326601b91

Observation 3fc296b6-4518-496a-9777-28985ae2a993 · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation wav2vec 2.0: A framework for self-supervised learning of speech representations

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.759927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.759927Z digest=sha256:5a2e68fbc380868f62edda84b8698660038632cd18e2e975df4ae4cd58a17dcf

Observation 22cf2238-fecc-42db-9abb-c068272c4fd0 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Learning transferable visual models from natural language supervision

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.763498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.763498Z digest=sha256:976e0106d2ef2fb15007d23e68ceffc6d714a4cb0ebd33cd1d2c4e79abfea079

Observation 288d04d8-49ef-45b5-9c95-023accc1c128 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation A simple framework for contrastive learning of visual representations

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.213294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.767042Z digest=sha256:c45079e03efbd8acbe4c99502b3f4ec34681cac61abad70cc5d6d216679c626a

Observation 2331e731-dce0-4751-8b81-1e065cf64687 · outbound

This paper cites Suggestive annotation: A deep active learning framework for biomedical image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Suggestive annotation: A deep active learning framework for biomedical image segmentation

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.770934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.770934Z digest=sha256:7a1976527a0ec4918f457953f3fceb61bf79e6212bc302afe4e6f54d7731bd25

Observation bb7e93ad-506d-4e37-b14d-41e926b329a5 · outbound

This paper cites Diminishing uncertainty within the training pool: Active learning for medical image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Diminishing uncertainty within the training pool: Active learning for medical image segmentation

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.197274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.775402Z digest=sha256:fb0f4db7143c6dc36b56e9e4fc51172a67754c68c33235738609b7c91df31617

Observation 6868091f-9105-483a-95aa-d7529d4efcd7 · outbound

This paper cites Hierarchical self-supervised learning for medical image segmentation based on multi-domain data aggregation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Hierarchical self-supervised learning for medical image segmentation based on multi-domain data aggregation

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.187467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.779228Z digest=sha256:f0b389d700c5190bc44359ff4aded5ce4368c5457ff2c3549057c2ddc01762d4

Observation 4cf7c405-423c-4536-8577-8c0607f95725 · outbound

This paper cites Supervised contrastive learning.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Supervised contrastive learning

Reference 74

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.782737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.782737Z digest=sha256:275c79e047e953ff0bbc4e93bdc809a9af454da8e02b6c0d4020f5c50e961dcc

Observation e2d8c5de-6ff3-4fbc-804d-fb756fd5e7c3 · outbound

This paper cites Deep residual learning for image recognition.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep residual learning for image recognition

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.786545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.786545Z digest=sha256:9bfa0ab14c77019c90678eed645f66ec3f24a5611c062849dcbc10c3c25e6387

Observation 9243e869-751d-4a07-b655-46c4986446ca · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation U-net: Convolutional networks for biomedical image segmentation

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.790132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.790132Z digest=sha256:f0197b1d57ac67fb16fb8156a5e8e00295d3a5356723a4ee152e42d4f978a53f

Observation 4efda970-5a76-4ef5-a067-81b813e86c90 · outbound

This paper cites Lvm-med: Learning large-scale self-supervised vision models for medical imaging via second-order graph matching.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Lvm-med: Learning large-scale self-supervised vision models for medical imaging via second-order graph matching

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.156928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.793388Z digest=sha256:181599bea06898ebb6197b96d16e94e226769cf0de25e5137a33c746ace6becf

Observation 79f93cbc-5a6f-41d4-894e-36ca918fb5ab · outbound

This paper cites Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved? IEEE transactions on medical imaging, 37(11):2514–2525, 2018.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved? IEEE transactions on medical imaging, 37(11):2514–2525, 2018

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.796740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.796740Z digest=sha256:de47874d2ae011f0cf3f8c92e5758ca3f4f64ebe6191709f626b6c3ae73573c2

Observation 08d74b8c-37e4-4e6e-ab02-9f070c411e33 · outbound

This paper cites Alper Selver, O˘guz Dicle, Mustafa Barı¸ s, and N.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Alper Selver, O˘guz Dicle, Mustafa Barı¸ s, and N

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.140552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.800559Z digest=sha256:fb7cf660411708c5e9de679b302fbbfae4f3771e74c510c27a05804c0d1b7e92

Observation ccf38707-e61a-4f46-872c-b75aa75eb9a8 · outbound

This paper cites Bayeseg: Bayesian modeling for medical image segmentation with interpretable generalizability, 2023.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Bayeseg: Bayesian modeling for medical image segmentation with interpretable generalizability, 2023

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.130611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.803727Z digest=sha256:7097c6617f4f2ac263ca5468a20bdd0f1b9a00ac8984af5efe0d11037e7d11a9

Observation 0598ff89-c2d5-4c86-8551-3d824342a263 · outbound

This paper cites Multivariate mixture model for myocardial segmentation combining multi- source images.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Multivariate mixture model for myocardial segmentation combining multi- source images

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.120247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.806398Z digest=sha256:7826ca8cac4b0cd2466db954aba29440ae63bde061505da68cf6177ddf848924

Observation bd3c5c17-cc4d-4c8d-a795-51bcebfb3fc2 · outbound

This paper cites Minimizing estimated risks on unlabeled data: A new formula- tion for semi-supervised medical image segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Minimizing estimated risks on unlabeled data: A new formula- tion for semi-supervised medical image segmentation

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.109148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.809489Z digest=sha256:268885b6348a03fdb6dc3bc603d99fe7fe3ca783bb59576fc8dbb3e7ffb0d854

Observation 41e3df8b-a875-4b64-b331-7a2aadd85d2e · outbound

This paper cites CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision

Reference 83

Resolution
verified exact
local_arxiv, observed 2026-08-12T13:58:53.887267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.812807Z digest=sha256:11ed5a9566937495d14492b207cd7c83feabdde4c757ef4546a0eac222a0c8c0

Observation 1415cff2-7bd8-47dd-b563-0246dc6bbf81 · outbound

This paper cites A benchmark dataset and evaluation methodology for video object segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation A benchmark dataset and evaluation methodology for video object segmentation

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.816677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.816677Z digest=sha256:bb143782b38cef4bece4e295b5fea1f0b82edca891dd2f894b9acdd8286902a9

Observation 64f37caf-1be4-4cb2-8d25-2c343a89fb7c · outbound

This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation The 2017 DAVIS Challenge on Video Object Segmentation

Reference 85

Resolution
unresolved
no resolver link, observed 2026-08-12T13:58:53.820229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:58:53.820229Z digest=sha256:effc7b4bdde46abdbcb3401d86bbf47cbd06b3b038b25501f1e0996926c5aaae

Observation 35774759-8cf3-49f3-bb60-863d924dc325 · outbound

This paper cites Reliable delineation of clinical target volumes for cervical cancer radiotherapy on ct/mr dual-modality images.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Reliable delineation of clinical target volumes for cervical cancer radiotherapy on ct/mr dual-modality images

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.090805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.824163Z digest=sha256:82634d3b3d7ebdbc871c45a76c0c4ec20a6a1b744e4d6112b16310540d9703ff

Observation 5e969f19-61fe-419b-b415-bb5033861aad · outbound

This paper cites Domain and User-Centered Machine Learning for Medical Image Analysis.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Domain and User-Centered Machine Learning for Medical Image Analysis

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.079905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.827671Z digest=sha256:3deb9f753588fd52133bf5afa21ced52c46b5ad42f84de5a5813f087f34a309d

Observation deb35c5f-e1a1-49d6-b579-dca9b55aedfb · outbound

This paper cites Deep learning algorithm for auto-delineation of high-risk oropharyngeal clinical target volumes with built-in dice similarity coefficient parameter optimization function.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Deep learning algorithm for auto-delineation of high-risk oropharyngeal clinical target volumes with built-in dice similarity coefficient parameter optimization function

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.068946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.831162Z digest=sha256:fb7bf0f7948d123ab6345e490c6710ef60a3f5ce95f579ae411bfc4befa13ade

Observation e4691c2a-c8bc-4328-8028-35763be2c596 · outbound

This paper cites Automatic detection of contouring errors using convolutional neural networks.

Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation Automatic detection of contouring errors using convolutional neural networks

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:58:54.057324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:58:53.834808Z digest=sha256:83eaa09d981337ed45ab2e041ac7d2976ded9c9e3aa36d0c58b3aa401bca34f3

Pith citing papers

No inbound Pith citation observations are available.