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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.

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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

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Source: cited_works

Reference resolution

89 of 89 outbound references displayed

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External citation measurements

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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

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

Reference 24

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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

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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

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

Reference 27

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

Reference 28

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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

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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

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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

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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

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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

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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

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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

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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

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.646638Z digest=sha256:450c002d123ed1aaf710544b5e121909abc13edd84c659e2d2fac75e22792105

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

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.656861Z digest=sha256:dece34a15d46c68b41bc6e3a1cec9a74063d667949b52dd68aba6ca552cee76d

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

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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 2026-08-13T06:32:02.005865+00:00.

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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

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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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.667988Z digest=sha256:aa2d7bae24f87baa4ae7646cea6785ff7e6e0b5f6abbfecde11ea9ce70822feb

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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.671531Z digest=sha256:4d296b042810856ac37fcc80a6c7edf354e174053b5f757e4fa98c5ce6630344

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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.676125Z digest=sha256:3f17b4401895edbcf5df9e25cdf5dd592994c0a72123daab0a62f3b254d92b69

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 2026-08-13T06:32:02.005865+00:00.

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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

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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 2026-08-13T06:32:02.005865+00:00.

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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

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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 2026-08-13T06:32:02.005865+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.691906Z digest=sha256:799085d26b78d32d4a97c615e71f4d511af0d4424dc9bbd66f012aa29d14bb73

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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.699061Z digest=sha256:8516c0c6191e561e5b114aeef50aa82b328daf033bcd0caf3490bd54f41f853a

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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.702593Z digest=sha256:e91c002ff8cb4952587ba1f393cf4f47229470a33a9129c89d37ca3113b3e0e6

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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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

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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 2026-08-13T06:32:02.005865+00:00.

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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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.716860Z digest=sha256:cf05b0c3f345f4806fcdf6dd6193ad44d0596505c2de0774c1dd58e7b4fdeeb1

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.719974Z digest=sha256:49afd6f9c3db10b43776c15f0fbf0c39a9e78561f0592b5202954979e94b9d54

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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.724926Z digest=sha256:43d73c9c28ad1ac118fd738dbc2c9578c46746b628437cd78600fde722f49084

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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.728403Z digest=sha256:d3125b684100eceb2aefba4d0fafebaa290de31bb5031c60f337c5162c1ab1fe

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

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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 2026-08-13T06:32:02.005865+00:00.

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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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.736563Z digest=sha256:4da395dfc46501e6e5c4bd076e78684b0ef10a06135e1cc7652da7414fd179d9

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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.740611Z digest=sha256:70d1f43e7d58b4f45dc0f478a1b58f8721c029782b880506b5133d1aec9a8a9d

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.748282Z digest=sha256:8005564e8d3e15bdedfafcc50c195cc85ae0b74092f3c5f00eebc3635842fe60

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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.751944Z digest=sha256:231fd96e00b5d0382e9cab0bbb58614a08cf04114e41498e8cc3973265169a12

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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.756232Z digest=sha256:70b93fa6005d01a592d155581e7363ce3ff6d677376184e613366b3a2a73db2f

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

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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

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.767042Z digest=sha256:0638f19c15cf02ce7b9b32bca2f4c5c0c4ed980a4b7f5325db4344dc7b1a459a

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

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

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Unavailable: canonical work link unavailable.

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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

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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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

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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

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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

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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

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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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

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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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

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T13:58:53.803727Z digest=sha256:c333332b212ddd40f6cfac03504d4c261ce1696a7c6a7fdaf84b7420599d2a31

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

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source=pdf_text observed=2026-08-12T13:58:53.806398Z digest=sha256:7dacf00a0ffcf4568bcaece724846de6618153ebc2ad8ebe2e9242e842fa1597

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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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

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

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source=pdf_text observed=2026-08-12T13:58:53.812807Z digest=sha256:5dc35cc3ad25b8b827f2e9305dc947056a3a273b183dfb45f515bdf1272eeb0a

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

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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

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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

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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

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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 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.827671Z digest=sha256:d820ea3bb7f1c041e05da4d6e8aaa5287e5628723153472c29e8ef33b7a05e1e

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:58:53.831162Z digest=sha256:13e4416f4b08d80f7c755146bb79062ca90657c920287f94d167f2e0fab8aa4b

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

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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 2026-08-13T06:32:02.005865+00:00.

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Pith citing papers

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