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Paper Citation Record · LEDGER

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation

As of 11 August 2026, this Paper Citation Record lists 100 of 109 outbound references and 0 inbound Pith citation observations for arXiv:2606.17406.

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

pith.paper-citation-record.v1
2606.17406 v1

Coverage vector

measured 100 of 109 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T02:16:27.651526Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

100 of 109 outbound references displayed

  • verified exact23
  • verified fuzzy0
  • unresolved72
  • parse uncertain1
  • malformed identifier0
  • metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 86c232cf-e851-4927-8da2-220efa66138d · outbound

This paper cites Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , month =.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , month =

Reference 1

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Observation 26f0146b-6b33-4d96-833c-1b0af578d449 · outbound

This paper cites 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , year =.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , year =

Reference 3

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Observation cc223131-da76-4994-ab7a-b652fd2f98ee · outbound

This paper cites ImageNet Classification with Deep Convolutional Neural Networks.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation ImageNet Classification with Deep Convolutional Neural Networks

Reference 4

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Observation 578d07ba-e064-4026-abba-b873b2ac21ef · outbound

This paper cites Content-Based Image Retrieval: Theory and Applications.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Content-Based Image Retrieval: Theory and Applications

Reference 7

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Observation c4f67dfb-11ee-4a86-9ff0-7c18685b6c19 · outbound

This paper cites Information fusion in content based image retrieval: A comprehensive overview , journal =.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Information fusion in content based image retrieval: A comprehensive overview , journal =

Reference 8

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Observation bebb87c4-8480-4233-addd-eca74f919772 · outbound

This paper cites A comprehensive survey and experimental comparison of graph-based approximate nearest neighbor search,.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation A comprehensive survey and experimental comparison of graph-based approximate nearest neighbor search,

Reference 9

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Observation 2042970f-e70e-488e-b540-369d310b0586 · outbound

This paper cites Contrastive learning: Big Data Foundations and Applications.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Contrastive learning: Big Data Foundations and Applications

Reference 10

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Observation 56adcb91-6a2a-4353-ad85-fcf4c9b5a822 · outbound

This paper cites Unsupervised metric learning by Self-Smoothing Operator , year=.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Unsupervised metric learning by Self-Smoothing Operator , year=

Reference 11

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Observation 46d12966-4461-41ef-950f-0be72dd48d97 · outbound

This paper cites Omohundro , title =.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Omohundro , title =

Reference 12

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation and Joel Carbonera

Reference 13

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation 2023 , issue_date =

Reference 14

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Observation a2cb3d85-0daa-4cef-a9af-66dec9c7288b · outbound

This paper cites EAI Endorsed Transactions on AI and Robotics , volume=.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation EAI Endorsed Transactions on AI and Robotics , volume=

Reference 15

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Unresolved cited work

Reference 16

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Unresolved cited work

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Unresolved cited work

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation He and X

Reference 19

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Unresolved cited work

Reference 20

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Observation 10808b62-52b0-4af4-94cd-274d74f12e0f · outbound

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Pattern Recognition , volume =

Reference 21

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Observation d245378a-1a03-4f48-9783-d52a923d3540 · outbound

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation International Conference on Multimedia Retrieval (ICMR) , year =

Reference 22

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Observation aa4ccdda-b30f-4a8a-9485-e69318f33571 · outbound

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation IEEE Transactiosn on Image Processing , volume =

Reference 23

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Relatório de Trabalho de Conclusão de Curso (Graduação em Ciência da Computação) , pages =

Reference 24

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation PyUDLF: A Python Framework for Unsupervised Distance Learning Tasks , year =

Reference 25

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation IEEE Conference on Computer Vision and Pattern Recognition , volume =

Reference 26

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation An Unsupervised Distance Learning Framework for Multimedia Retrieval , booktitle =

Reference 27

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation 2013 , issn =

Reference 28

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Torres, Ricardo , booktitle=

Reference 29

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation 2016 , note =

Reference 30

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation International Conference on Learning Representations , year=

Reference 31

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Web Image Re-Ranking Using Query-Specific Semantic Signatures , year=

Reference 32

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Tag-Based Image Search by Social Re-ranking , year=

Reference 33

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation International Conference on Learning Representations , year=

Reference 34

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation 2016 , note =

Reference 35

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Why ResNet Works? Residuals Generalize , year=

Reference 39

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation PyTorch: An Imperative Style, High-Performance Deep Learning Library , volume =

Reference 40

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale , journal =

Reference 41

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation ICCV , year=

Reference 42

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Journal of Imaging , VOLUME =

Reference 43

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Texture Feature Extraction Methods: A Survey , year=

Reference 45

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This paper cites A Deep Neural Network Combined CNN and GCN for Remote Sensing Scene Classification , year=.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation A Deep Neural Network Combined CNN and GCN for Remote Sensing Scene Classification , year=

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Observation 0479e7da-db64-483b-82dc-bb9168b40d72 · outbound

This paper cites Multiscale Graph Sample and Aggregate Network With Context-Aware Learning for Hyperspectral Image Classification , year=.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Multiscale Graph Sample and Aggregate Network With Context-Aware Learning for Hyperspectral Image Classification , year=

Reference 47

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Observation 7aeb66ab-473d-49e5-837d-27714a1e9b0e · outbound

This paper cites International Journal of Electrical and Computer Engineering , volume=.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation International Journal of Electrical and Computer Engineering , volume=

Reference 48

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Observation 74de57c2-6457-4659-b205-140014ba5bdf · outbound

This paper cites Attention Multihop Graph and Multiscale Convolutional Fusion Network for Hyperspectral Image Classification , year=.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Attention Multihop Graph and Multiscale Convolutional Fusion Network for Hyperspectral Image Classification , year=

Reference 51

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Understanding of a convolutional neural network , year=

Reference 53

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This paper cites Novel Dataset for Fine-Grained Image Categorization , year =.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Novel Dataset for Fine-Grained Image Categorization , year =

Reference 54

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Observation b106cdfd-8cc5-4cb0-b117-529de59c3c11 · outbound

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Unresolved cited work

Reference 56

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Observation 150aa323-6dff-432d-8ab8-8d8cf6b86b9e · outbound

This paper cites The Caltech-UCSD Birds-200-2011 Dataset , publisher=.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation The Caltech-UCSD Birds-200-2011 Dataset , publisher=

Reference 57

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This paper cites Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , month =.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , month =

Reference 59

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Observation 4447e0d7-0856-4f7c-97a7-635d133e2d2d · outbound

This paper cites Dual Path Networks , url =.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Dual Path Networks , url =

Reference 60

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Observation 11d70372-6d24-4b25-ae42-4dabe8ed94ab · outbound

This paper cites Transactions on Machine Learning Research , issn=.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Transactions on Machine Learning Research , issn=

Reference 61

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Observation 9917126b-e3a6-4bf7-9650-4f340581e574 · outbound

This paper cites and Feng, Jiashi and Yan, Shuicheng , title =.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation and Feng, Jiashi and Yan, Shuicheng , title =

Reference 62

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Observation 7b537394-d24f-4778-a763-a0b14c4a1413 · outbound

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , month =

Reference 63

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Observation c2c37652-e39d-44c0-a336-28bdbb2f2572 · outbound

This paper cites Torres, Ricardo , journal=.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Torres, Ricardo , journal=

Reference 64

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Observation caa48d2d-af3a-4987-8669-a48ad4ae62cf · outbound

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation International Conference on Learning Representations , year=

Reference 65

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Observation 99d694cb-c124-4e73-a75e-d12ad46450f7 · outbound

This paper cites Proceedings of the 36th International Conference on Machine Learning , pages =.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Proceedings of the 36th International Conference on Machine Learning , pages =

Reference 66

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Observation c9dfff82-d8d4-4cf5-8e23-fcf1d660875e · outbound

This paper cites Graph Neural Networks With Convolutional ARMA Filters , year=.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Graph Neural Networks With Convolutional ARMA Filters , year=

Reference 67

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Observation 8af9a678-9f61-493f-adb5-2ba31bcfd886 · outbound

This paper cites Feature Fusion for Graph Convolutional Networks in Semi-Supervised Image Classification , year=.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Feature Fusion for Graph Convolutional Networks in Semi-Supervised Image Classification , year=

Reference 68

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Observation e5242349-c516-4829-ad96-6df52c455e05 · outbound

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation 2002 , publisher=

Reference 69

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Observation cf56a00c-10f7-4660-a63f-5f187ffef462 · outbound

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation 2002 , publisher=

Reference 70

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Observation 775c4ad3-fc30-47e9-9fff-f6e478cb883f · outbound

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Computer Vision and Image Understanding , volume=

Reference 71

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Observation 5c8f9661-e89b-4977-bd4a-e12bfd998cf7 · outbound

This paper cites Understanding of a convolutional neural network.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Understanding of a convolutional neural network

Reference 74

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Observation 8d78805e-2ec9-4c13-a290-04fb5ffd176b · outbound

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Unresolved cited work

Reference 75

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Observation 1a66d5a5-cc86-4843-bc27-1e90479791ce · outbound

This paper cites Sci.1–1 URL http://dx.doi.org/10.1109/TPAMI.2021.3054830 27 ML4AtomsSix Open Questions for MLIPsAuthoret al.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Sci.1–1 URL http://dx.doi.org/10.1109/TPAMI.2021.3054830 27 ML4AtomsSix Open Questions for MLIPsAuthoret al

Reference 76

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Observation d32e5276-125f-4ad8-b44d-ddd4afeb81ae · outbound

This paper cites Semi-Supervised Learning.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Semi-Supervised Learning

Reference 77

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Observation b67389e5-995b-4177-9844-5a767754fcb6 · outbound

This paper cites Dual path networks.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Dual path networks

Reference 78

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Observation 0c1c588a-2249-4ee2-bbf7-72fa9c3ee17d · outbound

This paper cites View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation View Independent Vehicle Make, Model and Color Recognition Using Convolutional Neural Network

Reference 79

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 9f8da951-dc2e-472a-bf4a-0040253f5ecf · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Imagenet: A large-scale hierarchical image database

Reference 80

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Observation 21e6510a-b6ce-4868-b398-73add9758833 · outbound

This paper cites Multiscale graph sample and aggregate network with context-aware learning for hyperspectral image classification.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Multiscale graph sample and aggregate network with context-aware learning for hyperspectral image classification

Reference 81

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Observation 13e89e8e-491a-4276-b6de-681b3489a5b8 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 82

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local_arxiv, observed 2026-06-27T02:20:22.549054Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation f0f415b3-5b4b-4300-a8aa-6e85cf9fc2bd · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Fast Graph Representation Learning with PyTorch Geometric

Reference 83

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation dd894273-08ee-4e32-a1d5-e7bd811b530f · outbound

This paper cites O., Schwartz, W.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation O., Schwartz, W

Reference 84

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arxiv_id, observed 2026-06-27T02:20:22.551884Z

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Observation 9bbc1c2d-c7d6-4c8d-a714-defdbdf04f38 · outbound

This paper cites Combining neural networks with personalized pagerank for classification on graphs.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Combining neural networks with personalized pagerank for classification on graphs

Reference 85

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Observation 5ee31115-3bd1-4690-a768-576433cf2050 · outbound

This paper cites an unresolved cited work.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Unresolved cited work

Reference 86

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Observation caa9ab6f-20a4-4b80-b427-40eadcbb7ae2 · outbound

This paper cites Squeeze-and-excitation networks.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Squeeze-and-excitation networks

Reference 87

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Observation af833089-a001-43a4-8157-56d89383cb68 · outbound

This paper cites Texture feature extraction methods: A survey.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Texture feature extraction methods: A survey

Reference 88

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arxiv_id, observed 2026-06-27T02:20:22.511811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 39a83aa5-e5fe-40b2-bf79-a72ed74f64b4 · outbound

This paper cites Unsupervised metric learning by self-smoothing operator.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Unsupervised metric learning by self-smoothing operator

Reference 89

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Observation 11f6ffba-4e9c-4187-8be0-10af1374d201 · outbound

This paper cites Low-rank constraint based dual projections learning for dimensionality reduction.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Low-rank constraint based dual projections learning for dimensionality reduction

Reference 90

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arxiv_id, observed 2026-06-27T02:20:22.519954Z

Source-reported events for the cited work

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Observation 43fa54b6-8e7f-4e1d-ae10-5c34ae06d17d · outbound

This paper cites Novel dataset for fine-grained image categorization.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Novel dataset for fine-grained image categorization

Reference 91

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Observation cb62b6ad-91d8-4438-84ab-118c3df79917 · outbound

This paper cites Kipf and Max Welling.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Kipf and Max Welling

Reference 92

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Observation fa2683cb-6220-486c-a29a-349b016f4b09 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Imagenet classification with deep convolutional neural networks

Reference 93

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Observation ea68a1e8-5b2e-4bac-aa40-2b7aa9b9347b · outbound

This paper cites Neighbor embedding projection and graph convolutional networks for image classification.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Neighbor embedding projection and graph convolutional networks for image classification

Reference 94

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Observation 75de2478-82d6-424d-bb30-dcd507617374 · outbound

This paper cites A comparative study of rank aggregation methods for partial and top ranked lists in genomic applications.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation A comparative study of rank aggregation methods for partial and top ranked lists in genomic applications

Reference 95

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation a9653dad-e452-431c-8683-7070c623dbe3 · outbound

This paper cites Image retrieval based on multi-texton histogram.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Image retrieval based on multi-texton histogram

Reference 96

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Observation 808911f4-bb46-4f29-a305-0aa9b43632b8 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Swin transformer: Hierarchical vision transformer using shifted windows

Reference 97

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Observation 5fa16b81-6ea0-43d0-86d5-5d559444b77a · outbound

This paper cites A convnet for the 2020s.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation A convnet for the 2020s

Reference 98

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Observation 29cea8e3-8748-434a-8354-6c3a5d236d0e · outbound

This paper cites Mutlag, Shaker K.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Mutlag, Shaker K

Reference 99

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 9c5e8b1e-515c-4e9e-b456-928fd52868e7 · outbound

This paper cites A visual vocabulary for flower classification.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation A visual vocabulary for flower classification

Reference 100

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Observation 9bffdf1b-c52f-4d52-9d69-72d782cb0448 · outbound

This paper cites Omohundro.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Omohundro

Reference 101

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Observation 8e2bd1c9-70a9-4e7c-9175-ee40b90679b0 · outbound

This paper cites an unresolved cited work.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Unresolved cited work

Reference 102

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Observation 7407944b-6a34-425d-bd06-6a9fb4df5833 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Pytorch: An imperative style, high-performance deep learning library

Reference 103

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Observation 36b7ed6d-bd1f-4523-9db2-59e20d11be0c · outbound

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Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Unresolved cited work

Reference 104

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Observation 44036c25-4383-434a-bf64-489fa74a8551 · outbound

This paper cites Semi-supervised and active learning through manifold reciprocal knn graph for image retrieval.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Semi-supervised and active learning through manifold reciprocal knn graph for image retrieval

Reference 105

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Observation 499a8057-7760-438e-b1bd-947127f0151a · outbound

This paper cites A bfs-tree of ranking references for unsupervised manifold learning.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation A bfs-tree of ranking references for unsupervised manifold learning

Reference 106

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Observation 7e74735c-6223-47b1-8900-e2562731b679 · outbound

This paper cites Efficient rank-based diffusion process with assured convergence.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Efficient rank-based diffusion process with assured convergence

Reference 107

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Observation f2ea9478-ffac-481c-84b5-f5f1d1885f35 · outbound

This paper cites Information fusion in content based image retrieval: A comprehensive overview.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Information fusion in content based image retrieval: A comprehensive overview

Reference 108

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Observation 06e6820f-a350-4a84-abeb-5f431fba4d6c · outbound

This paper cites Combination of texture feature extraction and forward selection for one-class support vector machine improvement in self-portrait classification.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Combination of texture feature extraction and forward selection for one-class support vector machine improvement in self-portrait classification

Reference 109

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Observation c98e24dc-acbc-4a82-9b3b-f4eb89de1a26 · outbound

This paper cites Collective classification in network data.AI Magazine, 29(3):93, Sep.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Collective classification in network data.AI Magazine, 29(3):93, Sep

Reference 110

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Observation 09a4266d-57c9-46c4-8e79-bea544635112 · outbound

This paper cites Content-based image retrieval: Theory and applications.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Content-based image retrieval: Theory and applications

Reference 111

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source=arxiv_source observed=2026-06-27T02:16:27.651526Z digest=sha256:9329cbed69eee6aa084f500c0a6a2396193e29179d196cbfd033b50dc47c1259

Observation 10d4f707-1e71-44b3-b584-3060dc1bbde9 · outbound

This paper cites Contrastive learning: Big data foundations and applications.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation Contrastive learning: Big data foundations and applications

Reference 112

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Observation 859e297f-f5ee-4099-841e-9fc893d3a810 · outbound

This paper cites A Survey on Self-Supervised Representation Learning.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation A Survey on Self-Supervised Representation Learning

Reference 113

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arxiv_id, observed 2026-07-03T19:08:49.499119Z

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Observation aa25392f-0e2f-4567-a93d-10aef2c04abf · outbound

This paper cites An unsupervised distance learning framework for multimedia retrieval.

Graph Neural Networks for Semi-Supervised Image Classification with Multi-Feature Aggregation An unsupervised distance learning framework for multimedia retrieval

Reference 114

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Pith citing papers

No inbound Pith citation observations are available.