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Paper Citation Record · LEDGER

Domain Adaptation Techniques for Natural and Medical Image Classification

As of 21 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2508.20537.

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

pith.paper-citation-record.v1
2508.20537 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:50:33.198803Z

measured 50 of 50 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.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

50 of 50 outbound references displayed

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External citation measurements

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Outbound references

Observation d6435a91-13dc-4700-80e0-bf5290f1ca20 · outbound

This paper cites Unpaired,unsuperviseddomainadaptationassumesyourdomainsarealreadysimilar.

Domain Adaptation Techniques for Natural and Medical Image Classification Unpaired,unsuperviseddomainadaptationassumesyourdomainsarealreadysimilar

Reference 1

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Observation 2cd19d03-b4be-43ab-83ca-1b744de203c1 · outbound

This paper cites Simulations of common unsupervised domain adaptation algorithms for image classification.IEEE Transactions on Instrumentation and Measurement, 74:1–17, 2025.

Domain Adaptation Techniques for Natural and Medical Image Classification Simulations of common unsupervised domain adaptation algorithms for image classification.IEEE Transactions on Instrumentation and Measurement, 74:1–17, 2025

Reference 2

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Observation ed43e863-4ec9-462c-9076-9f311588a403 · outbound

This paper cites Domain adaptation in remote sensing image classification: A survey.

Domain Adaptation Techniques for Natural and Medical Image Classification Domain adaptation in remote sensing image classification: A survey

Reference 3

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Observation dbe38c19-7312-4cdd-9371-b4df022bf3cd · outbound

This paper cites Correlation alignment for unsupervised domain adaptation.Domain adaptation in computer vision applications, pages 153–171, 2017.

Domain Adaptation Techniques for Natural and Medical Image Classification Correlation alignment for unsupervised domain adaptation.Domain adaptation in computer vision applications, pages 153–171, 2017

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 1d89ffdb-6ff6-4eff-a780-854c1cde1419 · outbound

This paper cites Deep subdomain adaptation network for image classification.IEEE transactions on neural networks and learning systems, 32(4):1713–1722, 2020.

Domain Adaptation Techniques for Natural and Medical Image Classification Deep subdomain adaptation network for image classification.IEEE transactions on neural networks and learning systems, 32(4):1713–1722, 2020

Reference 5

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Source-reported events for the cited work

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Observation bfbc3962-6551-4677-bb53-730a20660b57 · outbound

This paper cites Unsuperviseddomainadaptationviadeepconditionaladaptationnetwork.

Domain Adaptation Techniques for Natural and Medical Image Classification Unsuperviseddomainadaptationviadeepconditionaladaptationnetwork

Reference 6

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Observation 5e380ba7-cb43-4ab1-8c1f-883863ce740d · outbound

This paper cites Deep CORAL: Correlation alignment for deep domain adaptation.

Domain Adaptation Techniques for Natural and Medical Image Classification Deep CORAL: Correlation alignment for deep domain adaptation

Reference 7

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 06abc1ab-9678-4efd-a8d0-cdf96af82fff · outbound

This paper cites Heterogeneousdomainadaptationviacorrelativeanddiscriminativefeature learning.

Domain Adaptation Techniques for Natural and Medical Image Classification Heterogeneousdomainadaptationviacorrelativeanddiscriminativefeature learning

Reference 8

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Observation 3733ca79-9f7b-4d81-afa2-9cd57bf63bf8 · outbound

This paper cites Weakly correlated multimodal domain adaptation for pattern classification.

Domain Adaptation Techniques for Natural and Medical Image Classification Weakly correlated multimodal domain adaptation for pattern classification

Reference 9

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Source-reported events for the cited work

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Observation bb8fbad7-38de-426b-8c31-acd8243ded80 · outbound

This paper cites Domain-adversarial training of neural networks.The journal of machine learning research, 17(1):2096–2030, 2016.

Domain Adaptation Techniques for Natural and Medical Image Classification Domain-adversarial training of neural networks.The journal of machine learning research, 17(1):2096–2030, 2016

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 42d7270a-1eb1-4145-a6d5-4e46cb558ce7 · outbound

This paper cites Reusing the task-specific classifier as a discriminator: Discriminator-free adversarial domain adaptation.

Domain Adaptation Techniques for Natural and Medical Image Classification Reusing the task-specific classifier as a discriminator: Discriminator-free adversarial domain adaptation

Reference 11

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Source-reported events for the cited work

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Observation c93eb15c-936c-41e5-8e1f-07ec2d339186 · outbound

This paper cites InProceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 3941–3950, 2020.

Domain Adaptation Techniques for Natural and Medical Image Classification InProceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 3941–3950, 2020

Reference 12

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation bd62a78a-36ed-4c09-a628-11d56dd90702 · outbound

This paper cites Faa-clip:Federatedadversarialadaptationofclip.

Domain Adaptation Techniques for Natural and Medical Image Classification Faa-clip:Federatedadversarialadaptationofclip

Reference 13

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Observation c0463437-b125-4c6a-ad4d-0e7abe265b6f · outbound

This paper cites Domain-guided conditional diffusion model for unsupervised domain adaptation.Neural Networks, 184:107031, 2025.

Domain Adaptation Techniques for Natural and Medical Image Classification Domain-guided conditional diffusion model for unsupervised domain adaptation.Neural Networks, 184:107031, 2025

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 38e9a3ca-8e59-41c3-87ae-4c963b874372 · outbound

This paper cites Multi-source domain adaptation by causal-guided adaptive multimodal diffusion networks.International Journal of Computer Vision, 133(7):4623–4645, 2025.

Domain Adaptation Techniques for Natural and Medical Image Classification Multi-source domain adaptation by causal-guided adaptive multimodal diffusion networks.International Journal of Computer Vision, 133(7):4623–4645, 2025

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 694c9b8e-f5c1-49a7-82bc-a9928cf55a39 · outbound

This paper cites Ddci: Unsupervised domain adaptation for remote sensing images based on diffusion causal distillation.IEEE Transactions on Geoscience and Remote Sensing, 63:1–12, 2025.

Domain Adaptation Techniques for Natural and Medical Image Classification Ddci: Unsupervised domain adaptation for remote sensing images based on diffusion causal distillation.IEEE Transactions on Geoscience and Remote Sensing, 63:1–12, 2025

Reference 16

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 0c60a0d7-9259-49c4-be8b-dd06d658990f · outbound

This paper cites Textadapter: Self-supervised domain adaptation for cross-domain text recognition.IEEE Transactions on Multimedia, 26:9854–9865, 2024.

Domain Adaptation Techniques for Natural and Medical Image Classification Textadapter: Self-supervised domain adaptation for cross-domain text recognition.IEEE Transactions on Multimedia, 26:9854–9865, 2024

Reference 17

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Observation d1d7f610-1db2-4039-8827-5bf45f3767ae · outbound

This paper cites Samda: Leveraging sam on few-shot domain adaptation for electronic microscopy segmentation.

Domain Adaptation Techniques for Natural and Medical Image Classification Samda: Leveraging sam on few-shot domain adaptation for electronic microscopy segmentation

Reference 18

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Source-reported events for the cited work

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Observation d03b1ad2-1d4e-4c91-a0cd-05ec22d89e39 · outbound

This paper cites Feature fusion transferability aware transformer for unsupervised domain adaptation.

Domain Adaptation Techniques for Natural and Medical Image Classification Feature fusion transferability aware transformer for unsupervised domain adaptation

Reference 19

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Source-reported events for the cited work

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Observation f500a9ce-a636-4959-b347-8fd7e2bff496 · outbound

This paper cites Robust unsupervised domain adaptation through negative-view regularization.

Domain Adaptation Techniques for Natural and Medical Image Classification Robust unsupervised domain adaptation through negative-view regularization

Reference 20

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Source-reported events for the cited work

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Observation 9fd3bbbc-72c1-41a1-b607-70f335af93dd · outbound

This paper cites Open-set domain adaptation with visual-language foundation models.Computer Vision and Image Understanding, 250:104230, 2025.

Domain Adaptation Techniques for Natural and Medical Image Classification Open-set domain adaptation with visual-language foundation models.Computer Vision and Image Understanding, 250:104230, 2025

Reference 21

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 4d1da1b5-ebc3-4812-b830-c74d6bd00b12 · outbound

This paper cites Adapting visual category models to new domains.

Domain Adaptation Techniques for Natural and Medical Image Classification Adapting visual category models to new domains

Reference 22

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Source-reported events for the cited work

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Observation a433d1ed-0d9b-4c34-b4f3-aecca541ff40 · outbound

This paper cites Reusing the task-specific classifier as a discriminator: Discriminator-freeadversarialdomainadaptation.

Domain Adaptation Techniques for Natural and Medical Image Classification Reusing the task-specific classifier as a discriminator: Discriminator-freeadversarialdomainadaptation

Reference 23

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation ce8263e3-ceca-40d5-9fd8-c16de2390fc3 · outbound

This paper cites A brief review of domain adaptation.Advances in data science and information engineering, pages 877–894, 2021.

Domain Adaptation Techniques for Natural and Medical Image Classification A brief review of domain adaptation.Advances in data science and information engineering, pages 877–894, 2021

Reference 24

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 7e8cb9b9-d5e5-49c9-82fa-c82f8d4e81f5 · outbound

This paper cites NeuralNetworks, page 106230, 2024.

Domain Adaptation Techniques for Natural and Medical Image Classification NeuralNetworks, page 106230, 2024

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a0274ada-ea08-42dd-aef6-271e0b2218bb · outbound

This paper cites Efficient unsupervised domain adaptation via self-supervised vision transformer and synergistic cross-domain alignment.

Domain Adaptation Techniques for Natural and Medical Image Classification Efficient unsupervised domain adaptation via self-supervised vision transformer and synergistic cross-domain alignment

Reference 26

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Source-reported events for the cited work

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Observation b1277000-520a-4e98-a90f-cb56140ac5e1 · outbound

This paper cites Large-scale machine learning with stochastic gradient descent.

Domain Adaptation Techniques for Natural and Medical Image Classification Large-scale machine learning with stochastic gradient descent

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 8fdc3337-f5eb-4c68-a290-a8d23e8a172e · outbound

This paper cites Visualizing data using t-SNE.Journal of machine learning research, 9(11), 2008.

Domain Adaptation Techniques for Natural and Medical Image Classification Visualizing data using t-SNE.Journal of machine learning research, 9(11), 2008

Reference 28

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Source-reported events for the cited work

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Observation 8bb8cf50-d025-487a-aa03-b1122adbaacc · outbound

This paper cites Analysis of representations for domain adaptation.Advances in neural information processing systems, 19, 2006.

Domain Adaptation Techniques for Natural and Medical Image Classification Analysis of representations for domain adaptation.Advances in neural information processing systems, 19, 2006

Reference 29

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Source-reported events for the cited work

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Observation 63e1280d-2379-42bd-94a6-9f3e7af7b57d · outbound

This paper cites Grad-CAM: Visual explanations from deep networks via gradient-based localization.

Domain Adaptation Techniques for Natural and Medical Image Classification Grad-CAM: Visual explanations from deep networks via gradient-based localization

Reference 30

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raw_fallback, observed 2026-08-15T16:50:33.485749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 6e79c3e0-4b0a-4af8-88a3-f7d22cdb5e0e · outbound

This paper cites Deep hashing network for unsupervised domain adaptation.

Domain Adaptation Techniques for Natural and Medical Image Classification Deep hashing network for unsupervised domain adaptation

Reference 31

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Source-reported events for the cited work

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Observation 5215ccbb-d456-431e-aff9-1aad4482d55c · outbound

This paper cites Themanyfacesofrobustness:Acriticalanalysisofout-of-distributiongeneralization.

Domain Adaptation Techniques for Natural and Medical Image Classification Themanyfacesofrobustness:Acriticalanalysisofout-of-distributiongeneralization

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 37a26ed2-fb71-4a70-b8d4-55b912f218e0 · outbound

This paper cites Learning robust global representations by penalizing local predictive power.

Domain Adaptation Techniques for Natural and Medical Image Classification Learning robust global representations by penalizing local predictive power

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 6bfc79c4-8aef-4b17-8bae-6c3006a927dc · outbound

This paper cites Adaptiope: A modern benchmark for unsupervised domain adaptation.

Domain Adaptation Techniques for Natural and Medical Image Classification Adaptiope: A modern benchmark for unsupervised domain adaptation

Reference 34

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 9c401b20-f056-41d8-b118-9aa3e168a627 · outbound

This paper cites COVIDNet-CT: A tailored deep convolutional neural network design for detection of COVID-19 cases from chest CT images.Frontiers in Medicine, 7:1025, 2020.

Domain Adaptation Techniques for Natural and Medical Image Classification COVIDNet-CT: A tailored deep convolutional neural network design for detection of COVID-19 cases from chest CT images.Frontiers in Medicine, 7:1025, 2020

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:50:33.428393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation e51a1349-fa3d-4285-99dc-ce1be20e0fed · outbound

This paper cites ChestX-ray8: Hospital-scale chest X-raydatabaseandbenchmarksonweakly-supervisedclassificationandlocalizationofcommonthoraxdiseases.

Domain Adaptation Techniques for Natural and Medical Image Classification ChestX-ray8: Hospital-scale chest X-raydatabaseandbenchmarksonweakly-supervisedclassificationandlocalizationofcommonthoraxdiseases

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:50:33.415878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 3dc9a128-947b-4cf2-baef-938ae7fc7916 · outbound

This paper cites Vision transformer and explainabletransferlearningmodelsforautodetectionofkidneycyst,stoneandtumorfromCT-radiography.

Domain Adaptation Techniques for Natural and Medical Image Classification Vision transformer and explainabletransferlearningmodelsforautodetectionofkidneycyst,stoneandtumorfromCT-radiography

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:50:33.402641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation e81ef36e-d976-42a5-9889-fb08b41ce68e · outbound

This paper cites Retinal fundus multi-disease image dataset (RFMiD): A dataset for multi-disease detection research.

Domain Adaptation Techniques for Natural and Medical Image Classification Retinal fundus multi-disease image dataset (RFMiD): A dataset for multi-disease detection research

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:50:33.389792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:50:33.152505Z digest=sha256:e12f85a30092b5d9f6fccf1820f7ac8d81725052796711ea5e9d154b32bacc44

Observation ee96ea80-23eb-4d05-814d-3915d53b4916 · outbound

This paper cites The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.Scientific data, 5(1):1–9, 2018.

Domain Adaptation Techniques for Natural and Medical Image Classification The ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions.Scientific data, 5(1):1–9, 2018

Reference 39

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unresolved
no resolver link, observed 2026-08-15T16:50:33.156541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:50:33.156541Z digest=sha256:a10d83b262a62f8e7b0e822ad61b97fe982aa347fdfe7a853a5fb2ed5d338fe4

Observation b2fc657d-7fc2-414d-bf91-1071bb9a66ec · outbound

This paper cites an unresolved cited work.

Domain Adaptation Techniques for Natural and Medical Image Classification Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-15T16:50:33.368439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:50:33.160534Z digest=sha256:f4429481b9bf2e97a7df5357b52826ca11c5290aaa81bd76dbd294220bae6638

Observation 42894100-2fb2-4440-acf5-c457ddb6f1f3 · outbound

This paper cites BCN20000: Dermoscopic Lesions in the Wild.

Domain Adaptation Techniques for Natural and Medical Image Classification BCN20000: Dermoscopic Lesions in the Wild

Reference 41

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unresolved
no resolver link, observed 2026-08-15T16:50:33.164488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:50:33.164488Z digest=sha256:d7e72ad28fc4fc0ce9185521d598954604c8527a86fea019c8f131d642e085d8

Observation 7b80841b-0e06-4cad-95be-ea6dee9b4e69 · outbound

This paper cites Deep residual learning for image recognition.

Domain Adaptation Techniques for Natural and Medical Image Classification Deep residual learning for image recognition

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T16:50:33.168920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:50:33.168920Z digest=sha256:f9e52e29cb61d38e669b9f81af806ab5b07bbd87e98ed0c50791667be988b0e1

Observation 0a8d422e-1681-4071-9a7a-264673123e54 · outbound

This paper cites Densely connected convolutional networks.

Domain Adaptation Techniques for Natural and Medical Image Classification Densely connected convolutional networks

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T16:50:33.172745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:50:33.172745Z digest=sha256:f83c1a4fb9985f7de2ba12a71f9f7dca6047cdad11032020f739b85bcb77de79

Observation b580aa9d-026f-467a-9f0c-a309241a2f47 · outbound

This paper cites Shufflenet:Anextremelyefficientconvolutionalneuralnetworkformobiledevices.

Domain Adaptation Techniques for Natural and Medical Image Classification Shufflenet:Anextremelyefficientconvolutionalneuralnetworkformobiledevices

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:50:33.338218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:50:33.176840Z digest=sha256:fc7af188ad241d21ebeedbb0efe16551234b192b9790e8741ef30b0cb655687b

Observation 0800f06b-1953-4ffe-9f7f-d89c7c8234ec · outbound

This paper cites MobileNetV2: Inverted residuals and linear bottlenecks.

Domain Adaptation Techniques for Natural and Medical Image Classification MobileNetV2: Inverted residuals and linear bottlenecks

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:50:33.323997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:50:33.180940Z digest=sha256:247b82088cdeb7f6fdb9b21caa20736129bcd55106923c4af5becefec264fb3a

Observation 1b3f643e-4f0b-48ab-969a-e4b3b535c02d · outbound

This paper cites Multi-source and multi-target domain adaptation based on dynamic generator with attention.IEEE Transactions on Multimedia, 26:6891–6905, 2024.

Domain Adaptation Techniques for Natural and Medical Image Classification Multi-source and multi-target domain adaptation based on dynamic generator with attention.IEEE Transactions on Multimedia, 26:6891–6905, 2024

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:50:33.310134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:50:33.184798Z digest=sha256:bce02758eb84bd076814d4d46515ed0b226282912e0541078b3114666f34abc9

Observation bb294023-36be-4e5e-bbb7-2c689814d10b · outbound

This paper cites Federated learning for healthcare applications.IEEE Internet of Things Journal, 11(5):7339–7358, 2024.

Domain Adaptation Techniques for Natural and Medical Image Classification Federated learning for healthcare applications.IEEE Internet of Things Journal, 11(5):7339–7358, 2024

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:50:33.297714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:50:33.188603Z digest=sha256:756bd40cd68930cf0b5c1c9e6ffcf094fe5830702378e7af10b8cbb5ee3ad935

Observation 5cd47494-5f43-4f5f-8057-75d0fab767d1 · outbound

This paper cites Adversarial domain adaptation with clip for few-shot image classification.

Domain Adaptation Techniques for Natural and Medical Image Classification Adversarial domain adaptation with clip for few-shot image classification

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:50:33.285167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T16:50:33.192445Z digest=sha256:319beae69363615846a3fa5b9665365663e71c360cdc8edf355fe6b0dc0d854f

Observation fbe34382-4b69-43e0-842f-73f6e907ff4e · outbound

This paper cites Calibratingdeepneuralnetworksusing focal loss.Advances in Neural Information Processing Systems, 33:15288–15299, 2020.

Domain Adaptation Techniques for Natural and Medical Image Classification Calibratingdeepneuralnetworksusing focal loss.Advances in Neural Information Processing Systems, 33:15288–15299, 2020

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T16:50:33.272716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 06fa506a-08b1-4da4-be2c-e8c5ce8ef876 · outbound

This paper cites Do CIFAR-10 Classifiers Generalize to CIFAR-10?.

Domain Adaptation Techniques for Natural and Medical Image Classification Do CIFAR-10 Classifiers Generalize to CIFAR-10?

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-15T16:50:33.198803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.