Paper Citation Record · LEDGER

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis

As of 24 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2504.19737.

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

pith.paper-citation-record.v1
2504.19737 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:48:09.876838Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

44 of 44 outbound references displayed

verified exact1
verified fuzzy37
unresolved6
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0df3f7ff-9e04-4dad-a01b-232c3091f600 · outbound

This paper cites Invariant Risk Minimization.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Invariant Risk Minimization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T05:48:09.747912Z

Source-reported events for the cited work

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Observation 6b8b9ec8-d0de-4283-9c98-883822ada1a5 · outbound

This paper cites Un- supervised learning of visual features by contrasting cluster assignments.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Un- supervised learning of visual features by contrasting cluster assignments

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T05:48:09.752070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df0f82e7-c59c-4ac6-99c6-9815b1839684 · outbound

This paper cites Lfme: A simple frame- work for learning from multiple experts in domain generalization.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Lfme: A simple frame- work for learning from multiple experts in domain generalization

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.238435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 17b9bf9d-8cfd-48a5-8d3f-39f8f550825d · outbound

This paper cites Do- main adaptation for semantic segmentation with maximum squares loss.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Do- main adaptation for semantic segmentation with maximum squares loss

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.228825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation db30fe39-dfaf-4dc9-ae77-cbc9171b8213 · outbound

This paper cites Functional map of the world.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Functional map of the world

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.221095Z

Source-reported events for the cited work

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Observation 31df3836-9aac-483d-8bbe-d0a4dd2f4ffd · outbound

This paper cites StyleAugment: Learning Texture De-biased Representations by Style Augmentation without Pre-defined Textures.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis StyleAugment: Learning Texture De-biased Representations by Style Augmentation without Pre-defined Textures

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:48:09.946496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 56ed3f54-fc2c-4c95-ab60-077112bca1e5 · outbound

This paper cites Urban change detection for multispectral earth observation using convolutional neural networks.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Urban change detection for multispectral earth observation using convolutional neural networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.215814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1cbcf614-3aee-42fb-9c8d-0d9768823e02 · outbound

This paper cites Panoptic segmentation of satellite image time se- ries with convolutional temporal attention networks.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Panoptic segmentation of satellite image time se- ries with convolutional temporal attention networks

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.209964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 12f64672-4b3f-45f1-8162-bcfd99a362d6 · outbound

This paper cites Multi-modal temporal attention mod- els for crop mapping from satellite time series.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Multi-modal temporal attention mod- els for crop mapping from satellite time series

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.202785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a4d131cb-7142-4026-b45b-b9480b4b07a3 · outbound

This paper cites ResNet10: A lightweight resid- ual network for remote sensing image classification.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis ResNet10: A lightweight resid- ual network for remote sensing image classification

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.194436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3c4bdd5c-4de0-48a4-8e0a-000300553579 · outbound

This paper cites Deep residual learning for image recogni- tion.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Deep residual learning for image recogni- tion

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.186614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 61a584e9-247c-49db-baf5-2cd409741774 · outbound

This paper cites Classhyper: Classmix-based hy- brid perturbations for deep semi-supervised seman- tic segmentation of remote sensing imagery.Remote Sensing, 14(4):879, 2022.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Classhyper: Classmix-based hy- brid perturbations for deep semi-supervised seman- tic segmentation of remote sensing imagery.Remote Sensing, 14(4):879, 2022

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.179881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7df79472-3cb4-4af8-a031-e94ceace6f77 · outbound

This paper cites Mixchannel: Advanced augmen- tation for multispectral satellite images.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Mixchannel: Advanced augmen- tation for multispectral satellite images

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.173117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0fede0d7-bcdc-4cef-a3a2-fda302de9d18 · outbound

This paper cites WILDS: A benchmark of in-the-wild distribution shifts.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis WILDS: A benchmark of in-the-wild distribution shifts

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.165868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dfadb4b9-8532-4871-9a0e-28ea7c4f063f · outbound

This paper cites Out- of-distribution generalization via risk extrapolation (rex).

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Out- of-distribution generalization via risk extrapolation (rex)

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.158642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f24f6b97-b209-470c-b4c4-99b0d650b177 · outbound

This paper cites Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.151469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6854e035-a082-424b-a350-663debf8bda7 · outbound

This paper cites Domain Generalization using Pretrained Models without Fine-tuning.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Domain Generalization using Pretrained Models without Fine-tuning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T05:48:09.798198Z

Source-reported events for the cited work

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Observation 8d356a8f-a3a5-4e6f-b410-1d702a1cd899 · outbound

This paper cites Conditional adversarial domain adaptation.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Conditional adversarial domain adaptation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.144515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f8d0b43c-87b9-4fca-bfcd-c3bbe3313522 · outbound

This paper cites Global road extraction using a pseudo-label guided frame- work: from benchmark dataset to cross-region semi- supervised learning.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Global road extraction using a pseudo-label guided frame- work: from benchmark dataset to cross-region semi- supervised learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.136754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6b6774bb-bbbe-44b5-82a1-caeea96b53e3 · outbound

This paper cites Change-aware sampling and contrastive learning for satellite images.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Change-aware sampling and contrastive learning for satellite images

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.129878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 889183aa-5ab9-419c-bd80-87c05f5a3dab · outbound

This paper cites Seasonal contrast: Unsupervised pre-training from uncurated remote sensing data.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Seasonal contrast: Unsupervised pre-training from uncurated remote sensing data

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.122974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 28a73441-9560-4f6f-bdfc-f0c68bb17300 · outbound

This paper cites Geo- multitasknet: remote sensing unsupervised domain adaptation using geographical coordinates.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Geo- multitasknet: remote sensing unsupervised domain adaptation using geographical coordinates

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.115200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e61f47bf-3f44-46a4-b01c-7eda5b8bd1e5 · outbound

This paper cites Timematch: Unsupervised cross-region adaptation by temporal shift estimation.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Timematch: Unsupervised cross-region adaptation by temporal shift estimation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.106554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8524fb50-51d8-4d95-a39b-714ac2df1b70 · outbound

This paper cites ClassMix: Segmentation- based data augmentation for semi-supervised learn- ing.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis ClassMix: Segmentation- based data augmentation for semi-supervised learn- ing

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.099782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ac88fa63-f390-4151-82d9-61016f524fdc · outbound

This paper cites Focal loss for dense object detection.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Focal loss for dense object detection

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.090382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2f691c55-0bbb-4ed1-b128-90703635c1ec · outbound

This paper cites Extending the WILDS benchmark for unsu- pervised adaptation.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Extending the WILDS benchmark for unsu- pervised adaptation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.082392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 82db0b67-e66b-463d-beca-98b387f21af2 · outbound

This paper cites Universal domain adaptation through self supervision.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Universal domain adaptation through self supervision

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.072228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7b68816c-484e-47c2-8eb4-cdc66d79e9df · outbound

This paper cites Parameter efficient self-supervised geospatial domain adaptation.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Parameter efficient self-supervised geospatial domain adaptation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.064885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c767ba35-3099-4cd2-9b6c-166d9014a442 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T05:48:09.838878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c6f8bbc-4518-4bbe-a89f-c4a614620acc · outbound

This paper cites Fixmatch: Simplifying semi-supervised learning with consistency and confidence.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Fixmatch: Simplifying semi-supervised learning with consistency and confidence

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.058481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a4622d05-0289-406c-bc00-ce216ae4e509 · outbound

This paper cites Deep CORAL: Cor- relation alignment for deep domain adaptation.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Deep CORAL: Cor- relation alignment for deep domain adaptation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.049583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0d4ee3ef-3b36-473e-9cf2-ac29a2dc8d80 · outbound

This paper cites StandardGAN: Multi- source domain adaptation for semantic segmentation of very high resolution satellite images by data stan- dardization.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis StandardGAN: Multi- source domain adaptation for semantic segmentation of very high resolution satellite images by data stan- dardization

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.039584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8e6f191e-ec0d-4e62-96fe-0159aa2b6a13 · outbound

This paper cites DynamicEarthNet: Daily multi-spectral satellite dataset for semantic change segmentation.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis DynamicEarthNet: Daily multi-spectral satellite dataset for semantic change segmentation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.033710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 56ef5ca9-95e4-45db-a336-8f53cc44ef29 · outbound

This paper cites The multi-temporal urban development SpaceNet dataset.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis The multi-temporal urban development SpaceNet dataset

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.027353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 129a10de-a0d3-4b0b-842b-82d02153811c · outbound

This paper cites Pixel-wise Agricultural Image Time Series Classification: Comparisons and a Deformable Prototype-based Approach.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Pixel-wise Agricultural Image Time Series Classification: Comparisons and a Deformable Prototype-based Approach

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-16T05:48:09.854450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 262830d1-bb18-406c-a69a-a016b9a627d8 · outbound

This paper cites Satellite Image Time Series Semantic Change Detection: Novel Architecture and Analysis of Domain Shift.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Satellite Image Time Series Semantic Change Detection: Novel Architecture and Analysis of Domain Shift

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T05:48:09.857223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9385a23e-5a65-48f5-ab73-0f996f252d40 · outbound

This paper cites Advent: Adver- sarial entropy minimization for domain adaptation in semantic segmentation.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Advent: Adver- sarial entropy minimization for domain adaptation in semantic segmentation

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.020332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 98c85a6f-3751-4d32-9dd3-62a0eea21760 · outbound

This paper cites Self-training with noisy student im- proves imagenet classification.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Self-training with noisy student im- proves imagenet classification

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.012685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 83fa0633-2357-48eb-99bc-dd53ec8e5c09 · outbound

This paper cites Neural plasticity-inspired founda- tion model for observing the earth crossing modal- ities.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Neural plasticity-inspired founda- tion model for observing the earth crossing modal- ities

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:10.004717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 075e42cb-1a96-4c70-8171-b20db1f316f8 · outbound

This paper cites Improving domain generalization with domain relations.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Improving domain generalization with domain relations

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:09.996785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 81453122-b149-4275-9e99-40f1f363ec29 · outbound

This paper cites An empirical study on data augmen- tation for pixel-wise satellite image time series clas- sification and cross-year adaptation.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis An empirical study on data augmen- tation for pixel-wise satellite image time series clas- sification and cross-year adaptation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:09.988138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a2c30847-40ab-4e5b-bcba-7ab02e29548e · outbound

This paper cites Domain adaptive remote sensing image semantic segmentation with prototype guidance.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Domain adaptive remote sensing image semantic segmentation with prototype guidance

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:09.979949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a56639c9-86d9-4801-afd0-71b8ab971112 · outbound

This paper cites Land cover mapping from multiple complementary ex- perts under heavy class imbalance.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Land cover mapping from multiple complementary ex- perts under heavy class imbalance

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:09.971733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 12964a7c-cdfb-44b8-8fb2-5088ed2da9bd · outbound

This paper cites Contrastive learning for la- bel efficient semantic segmentation.

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis Contrastive learning for la- bel efficient semantic segmentation

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:48:09.962534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.