Hailiang Ye

978 total citations
51 papers, 686 citations indexed

About

Hailiang Ye is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Artificial Intelligence. According to data from OpenAlex, Hailiang Ye has authored 51 papers receiving a total of 686 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Computer Vision and Pattern Recognition, 19 papers in Computational Mechanics and 18 papers in Artificial Intelligence. Recurrent topics in Hailiang Ye's work include 3D Shape Modeling and Analysis (14 papers), 3D Surveying and Cultural Heritage (13 papers) and Remote-Sensing Image Classification (9 papers). Hailiang Ye is often cited by papers focused on 3D Shape Modeling and Analysis (14 papers), 3D Surveying and Cultural Heritage (13 papers) and Remote-Sensing Image Classification (9 papers). Hailiang Ye collaborates with scholars based in China, Australia and Macao. Hailiang Ye's co-authors include Feilong Cao, Bing Yang, Hong Li, Dianhui Wang, C. L. Philip Chen, Ming Li, Wenhui Guo, Chenglin Wen, Yuzhi Song and Feng Zhang and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Image Processing and Expert Systems with Applications.

In The Last Decade

Hailiang Ye

47 papers receiving 675 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hailiang Ye China 13 300 245 145 145 57 51 686
Michal Haindl Czechia 15 506 1.7× 77 0.3× 119 0.8× 119 0.8× 30 0.5× 86 730
Xiaolong Fan China 15 222 0.7× 133 0.5× 150 1.0× 81 0.6× 142 2.5× 31 564
Shanmin Pang China 17 475 1.6× 245 1.0× 68 0.5× 112 0.8× 27 0.5× 60 731
Zhengqin Li United States 12 897 3.0× 82 0.3× 196 1.4× 234 1.6× 76 1.3× 24 1.2k
M. Petrou United Kingdom 15 866 2.9× 153 0.6× 65 0.4× 197 1.4× 17 0.3× 69 1.1k
Florinel-Alin Croitoru Romania 4 348 1.2× 222 0.9× 39 0.3× 65 0.4× 10 0.2× 7 849
Vlad Hondru Romania 3 341 1.1× 206 0.8× 38 0.3× 65 0.4× 9 0.2× 5 832
Yi Wei China 15 562 1.9× 95 0.4× 185 1.3× 87 0.6× 95 1.7× 31 813
Andrés Romero France 6 594 2.0× 149 0.6× 94 0.6× 76 0.5× 12 0.2× 14 869

Countries citing papers authored by Hailiang Ye

Since Specialization
Citations

This map shows the geographic impact of Hailiang Ye's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hailiang Ye with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hailiang Ye more than expected).

Fields of papers citing papers by Hailiang Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hailiang Ye. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hailiang Ye. The network helps show where Hailiang Ye may publish in the future.

Co-authorship network of co-authors of Hailiang Ye

This figure shows the co-authorship network connecting the top 25 collaborators of Hailiang Ye. A scholar is included among the top collaborators of Hailiang Ye based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hailiang Ye. Hailiang Ye is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cao, Feilong, et al.. (2025). A Joint Multiscale Graph Attention and Classify-Driven Autoencoder Framework for Hyperspectral Unmixing. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–14.
2.
Cao, Feilong, et al.. (2024). A fast hypergraph neural network with detail preservation for hyperspectral image classification. International Journal of Remote Sensing. 45(9). 3104–3128. 2 indexed citations
3.
Cao, Feilong, et al.. (2024). A Multi-View Graph Contrastive Learning Framework for Defending Against Adversarial Attacks. IEEE Transactions on Emerging Topics in Computational Intelligence. 8(6). 4022–4032.
4.
Ye, Hailiang, et al.. (2024). Label-Decoupled Medical Image Segmentation With Spatial-Channel Graph Convolution and Dual Attention Enhancement. IEEE Journal of Biomedical and Health Informatics. 28(5). 2830–2841. 8 indexed citations
5.
Cao, Feilong, et al.. (2023). Triplet teaching graph contrastive networks with self-evolving adaptive augmentation. Pattern Recognition. 142. 109687–109687. 5 indexed citations
6.
Ye, Hailiang, et al.. (2023). Two-stream coupling network with bidirectional interaction between structure and texture for image inpainting. Expert Systems with Applications. 231. 120700–120700. 7 indexed citations
7.
Zhu, Lei, et al.. (2023). A new method for two-stage partial-to-partial 3D point cloud registration: multi-level interaction perception. International Journal of Machine Learning and Cybernetics. 14(11). 3765–3781. 2 indexed citations
8.
Cao, Feilong, Lei Zhu, Hailiang Ye, Chenglin Wen, & Qinghua Zhang. (2023). A new method for point cloud registration: Adaptive relation-oriented convolution and recurrent correspondence-walk. Knowledge-Based Systems. 284. 111280–111280. 5 indexed citations
9.
Ye, Hailiang, et al.. (2023). ICCL: Independent and Correlative Correspondence Learning for few-shot image classification. Knowledge-Based Systems. 266. 110412–110412. 25 indexed citations
10.
Liu, Siqi, Hailiang Ye, Bing Yang, Ming Li, & Feilong Cao. (2023). A joint parcellation and boundary network with multi-rate-shared dilated graph attention for cortical surface parcellation. Medical & Biological Engineering & Computing. 62(2). 537–549.
11.
Yang, Bing, Hailiang Ye, Ming Li, Feilong Cao, & Shirui Pan. (2023). GoLoG: Global-to-Local Decoupling Graph Network With Joint Optimization for Hyperspectral Image Classification. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–14. 9 indexed citations
12.
Ye, Hailiang, et al.. (2022). A Novel Local–Global Graph Convolutional Method for Point Cloud Semantic Segmentation. IEEE Transactions on Neural Networks and Learning Systems. 35(4). 4798–4812. 54 indexed citations
13.
Yang, Bing, Feilong Cao, & Hailiang Ye. (2022). A Novel Method for Hyperspectral Image Classification: Deep Network With Adaptive Graph Structure Integration. IEEE Transactions on Geoscience and Remote Sensing. 60. 1–12. 36 indexed citations
14.
Ye, Hailiang, et al.. (2022). A novel method for point cloud completion: Adaptive region shape fusion network. Knowledge-Based Systems. 255. 109770–109770. 3 indexed citations
15.
Zhang, Lichao, et al.. (2021). A blind watermarking system based on deep learning model. 1208–1213. 4 indexed citations
16.
Ye, Hailiang, et al.. (2021). Multiscale fused network with additive channel–spatial attention for image segmentation. Knowledge-Based Systems. 214. 106754–106754. 59 indexed citations
17.
Ye, Hailiang, Yi Wang, & Feilong Cao. (2021). A novel meta-learning framework: Multi-features adaptive aggregation method with information enhancer. Neural Networks. 144. 755–765. 9 indexed citations
18.
Ye, Hailiang, Hong Li, & C. L. Philip Chen. (2020). Adaptive Deep Cascade Broad Learning System and Its Application in Image Denoising. IEEE Transactions on Cybernetics. 51(9). 4450–4463. 73 indexed citations
19.
Ye, Hailiang, Hong Li, Feilong Cao, & Liming Zhang. (2019). A Hybrid Truncated Norm Regularization Method for Matrix Completion. IEEE Transactions on Image Processing. 28(10). 5171–5186. 13 indexed citations
20.
Ye, Hailiang, Hong Li, Bing Yang, Feilong Cao, & Yuanyan Tang. (2019). A Novel Rank Approximation Method for Mixture Noise Removal of Hyperspectral Images. IEEE Transactions on Geoscience and Remote Sensing. 57(7). 4457–4469. 28 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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2026