Paper Citation Record · LEDGER

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation

As of 12 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2412.06470.

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

pith.paper-citation-record.v1
2412.06470 v2

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:40:06.722890Z

measured 39 of 39 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

39 of 39 outbound references displayed

verified exact11
verified fuzzy18
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2481e214-07e3-4f65-8b79-828249520b3a · outbound

This paper cites an unresolved cited work.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Unresolved cited work

Reference 1

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Observation afd34716-d259-4b6a-ade5-7aeb4ac6c3fc · outbound

This paper cites Ac- tive learning for imbalanced datasets, 2020.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Ac- tive learning for imbalanced datasets, 2020

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:07.658631Z

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Observation 4627288f-a27b-4ac5-bf56-3afac6a108aa · outbound

This paper cites Minority Class Oriented Active Learning for Imbalanced Datasets.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Minority Class Oriented Active Learning for Imbalanced Datasets

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:40:07.265018Z

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Observation bb6d473c-6c47-4d08-a226-33c3ca59f4b9 · outbound

This paper cites 2018 Robotic Scene Segmentation Challenge.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation 2018 Robotic Scene Segmentation Challenge

Reference 4

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Observation 606b5fd5-a660-4fcc-bc93-7d7d923b99bc · outbound

This paper cites Active learning for imbalanced data under cold start.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Active learning for imbalanced data under cold start

Reference 5

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Observation 84e588f6-fa4c-4739-9b1c-15a01ae9b2f4 · outbound

This paper cites Active Class Incremental Learning for Imbalanced Datasets.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Active Class Incremental Learning for Imbalanced Datasets

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:40:07.183519Z

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Observation 6ca3ddd0-0695-4113-b6ee-3ae9e309539b · outbound

This paper cites Class-balanced active learn- ing for image classification, 2021.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Class-balanced active learn- ing for image classification, 2021

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:07.638614Z

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Observation a17b58a1-16d2-4ad8-b074-9f17fecf8a2f · outbound

This paper cites Revisiting superpixels for active learning in semantic seg- mentation with realistic annotation costs.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Revisiting superpixels for active learning in semantic seg- mentation with realistic annotation costs

Reference 8

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Observation ab8f13d4-41ea-40c6-b385-dab2f3101492 · outbound

This paper cites Reinforced active learning for image segmentation.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Reinforced active learning for image segmentation

Reference 9

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Source-reported events for the cited work

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Observation 2d530fb5-38a8-4327-b7d5-cb0ba9cceb82 · outbound

This paper cites Rethinking Atrous Convolution for Semantic Image Segmentation.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Rethinking Atrous Convolution for Semantic Image Segmentation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T19:40:06.558110Z

Source-reported events for the cited work

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Observation 9166a30c-f7e3-47c2-98d7-a01021085c51 · outbound

This paper cites MetaBox+: A new Region Based Active Learning Method for Semantic Segmentation using Priority Maps.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation MetaBox+: A new Region Based Active Learning Method for Semantic Segmentation using Priority Maps

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:40:07.114122Z

Source-reported events for the cited work

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Observation 5fb7731a-2b90-4436-bb16-21fcbde6bb1b · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation The cityscapes dataset for semantic urban scene understanding

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:07.598363Z

Source-reported events for the cited work

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Observation bfa716c1-18b5-44a4-8c42-1a398da8c445 · outbound

This paper cites Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling

Reference 13

Resolution: metadata mismatch; local_arxiv, observed 2026-08-11T19:40:07.086784Z

Source-reported events for the cited work

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Observation 4d79d95e-4fae-408d-875f-f329b31612c6 · outbound

This paper cites Seeds: Superpixels extracted via energy- driven sampling, 2013.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Seeds: Superpixels extracted via energy- driven sampling, 2013

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:07.578245Z

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Observation 9bb006d7-599b-49a7-9c5b-8784a43d84b4 · outbound

This paper cites Everingham, L.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Everingham, L

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:07.557568Z

Source-reported events for the cited work

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Observation 1fa2708f-66d9-446b-803c-09bae217c19e · outbound

This paper cites Importance of Self-Consistency in Active Learning for Semantic Segmentation.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Importance of Self-Consistency in Active Learning for Semantic Segmentation

Reference 16

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Source-reported events for the cited work

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Observation f0136ab7-11c7-4f78-a3e8-5fd11635f497 · outbound

This paper cites Active learning for semantic segmentation with multi-class label query, 2023.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Active learning for semantic segmentation with multi-class label query, 2023

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:07.536075Z

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Observation 88f70b9c-956f-4b54-a2b6-bb0da87b0540 · outbound

This paper cites Joshi, Fatih Porikli, and Nikolaos Papanikolopoulos.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Joshi, Fatih Porikli, and Nikolaos Papanikolopoulos

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:07.513259Z

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Observation 05efcb5d-adda-438c-9c5d-d3c1fc528bec · outbound

This paper cites Hegde, V.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Hegde, V

Reference 19

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Source-reported events for the cited work

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Observation 53d373a5-f32f-466d-bd3f-26eef21db24e · outbound

This paper cites Simple Does It: Weakly Supervised Instance and Semantic Segmentation.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Simple Does It: Weakly Supervised Instance and Semantic Segmentation

Reference 20

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Observation ed17f6be-a31b-42e7-81a7-2e5cdd6b3cdd · outbound

This paper cites Adaptive superpixel for active learning in semantic segmentation, 2023.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Adaptive superpixel for active learning in semantic segmentation, 2023

Reference 21

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Source-reported events for the cited work

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Observation 61a0b380-3a29-4481-a0ab-3296a9d72f31 · outbound

This paper cites Kingma and Jimmy Ba.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Kingma and Jimmy Ba

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:07.450668Z

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Observation 918283d6-5d7c-42ff-ada7-b3553d2372d5 · outbound

This paper cites Clinical: Targeted active learning for imbalanced medical image clas- sification, 2022.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Clinical: Targeted active learning for imbalanced medical image clas- sification, 2022

Reference 23

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Observation d6ebfd56-b7cb-4831-aff6-0dabcc394780 · outbound

This paper cites Weakly supervised segmentation of small buildings with point labels.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Weakly supervised segmentation of small buildings with point labels

Reference 24

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Source-reported events for the cited work

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Observation 4ff0a631-0066-4d4b-8c3f-e8623052e793 · outbound

This paper cites DIAL: Deep Interactive and Active Learning for Semantic Segmentation in Remote Sensing.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation DIAL: Deep Interactive and Active Learning for Semantic Segmentation in Remote Sensing

Reference 25

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Source-reported events for the cited work

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Observation d10624af-6d14-407f-b28c-6bb719ec511b · outbound

This paper cites CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation

Reference 26

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Observation aaec3a74-0846-4867-9534-06fb2a3eb94c · outbound

This paper cites Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Weakly-Supervised Semantic Segmentation by Learning Label Uncertainty

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:40:06.944057Z

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Observation c8fa8f73-a125-4874-bccd-4ceebb6c2e13 · outbound

This paper cites Reducing Annotating Load: Active Learning with Synthetic Images in Surgical Instrument Segmentation.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Reducing Annotating Load: Active Learning with Synthetic Images in Surgical Instrument Segmentation

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:40:06.916612Z

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Observation 748ed1d5-8d46-4475-8baf-df490d768149 · outbound

This paper cites What's the Point: Semantic Segmentation with Point Supervision.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation What's the Point: Semantic Segmentation with Point Supervision

Reference 29

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Observation 9577ebd0-b97b-4b38-afab-c3bc3015783e · outbound

This paper cites A mathematical theory of commu- nication.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation A mathematical theory of commu- nication

Reference 30

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Observation 0a99fc52-5906-4c41-a31e-d6b0d587f0d1 · outbound

This paper cites ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:40:06.871405Z

Source-reported events for the cited work

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Observation 0ed391f5-1ea4-48ff-a780-cc765f11b358 · outbound

This paper cites Variational Adversarial Active Learning.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Variational Adversarial Active Learning

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:40:06.846275Z

Source-reported events for the cited work

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Observation 46505909-cca5-42ea-997d-d3ce3c32fd8d · outbound

This paper cites MEAL: Manifold Embedding-based Active Learning.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation MEAL: Manifold Embedding-based Active Learning

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:40:06.820525Z

Source-reported events for the cited work

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Observation 687a51ad-4cce-4224-b35c-0fae0cfea4af · outbound

This paper cites Segmenter: Transformer for Semantic Segmentation.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Segmenter: Transformer for Semantic Segmentation

Reference 34

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Source-reported events for the cited work

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Observation 26ff0301-fb77-44f7-b928-d4b9f584d9ac · outbound

This paper cites Correlation-aware active learn- ing for surgery video segmentation, 2023.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Correlation-aware active learn- ing for surgery video segmentation, 2023

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:07.354610Z

Source-reported events for the cited work

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Observation 497f045b-9dc0-47de-93d6-bd63a7cee023 · outbound

This paper cites Towards fewer annotations: Active learning via region impurity and prediction uncertainty for domain adaptive semantic segmentation, 2022.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Towards fewer annotations: Active learning via region impurity and prediction uncertainty for domain adaptive semantic segmentation, 2022

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:07.332821Z

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.

Observation fcca782b-ebe3-4033-a54c-012ac166ca40 · outbound

This paper cites Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-11T19:40:06.774342Z

Source-reported events for the cited work

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Observation c784ef8a-3a9f-4080-91d2-2de6d52d7b91 · outbound

This paper cites Algorithm selection for deep active learning with imbalanced datasets, 2023.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Algorithm selection for deep active learning with imbalanced datasets, 2023

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:07.309393Z

Source-reported events for the cited work

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Observation 4a9464a0-c22b-4a5b-aaf6-6cc33219f786 · outbound

This paper cites Dsal: Deeply supervised active learning from strong and weak labelers for biomedical image segmentation.

Active Learning with Context Sampling and One-vs-Rest Entropy for Semantic Segmentation Dsal: Deeply supervised active learning from strong and weak labelers for biomedical image segmentation

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T19:40:07.287797Z

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.

Pith citing papers

No inbound Pith citation observations are available.