📝 Publications

A new strategy of graph structure attack: Multi-view perturbation candidate edge learning [paper]
Feilong Cao, Qiyang Chen, Hailiang Ye*
IEEE Transactions on Network Science and Engineering, 2024, doi: 10.1109/TNSE.2024.3400860.

A multi-view graph contrastive learning framework for defending against adversarial attacks [paper]
Felong Cao, Xing Ye, Hailiang Ye*
IEEE Transactions on Emerging Topics in Computational Intelligence, 2024, doi: 10.1109/TETCI.2024.3382230.

SharpGConv: A novel graph method with plug-and-play sharpening convolution for point cloud registration [paper]
Feilong Cao, Lingpeng Wang, Hailiang Ye*
IEEE Transactions on Circuits and Systems for Video Technology, 2024, doi: 10.1109/TCSVT.2024.3369468.

A novel local-global graph convolutional method for point cloud semantic segmentation [paper]
Zijin Du, Hailiang Ye, Feilong Cao
IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(4): 4798-4812.

Label-decoupled medical image segmentation with spatial-channel graph convolution and dual attention enhancement [paper]
Qingting Jiang, Hailiang Ye*, Bing Yang, Feilong Cao*
IEEE Journal of Biomedical and Health Informatics, 2024, 28(5): 2830-2841.

A new method for point cloud registration: Adaptive relation-oriented convolution and recurrent correspondence-walk [paper]
Feilong Cao, Lei Zhu, Hailiang Ye, Chenglin Wen, Qinghua Zhang
Knowledge-Based Systems, 2024, 284: 111280.

Node-personalized multi-graph convolutional networks for recommendation [paper]
Tiantian Zhou, Hailiang Ye, Feilong Cao
Neural Networks, 2024, 173: 106169.

An effective targeted label adversarial attack on graph neural networks by strategically allocating the attack budget [paper]
Feilong Cao, Qiyang Chen, Hailiang Ye
Knowledge-Based Systems, 2024, 293: 111689.

Two-view point cloud registration network: Feature and geometry [paper]
Lingpeng Wang, Bing Yang, Hailiang Ye, Feilong Cao
Applied Intelligence, 2024, 54: 3135-3151.

A joint parcellation and boundary network with multi-rate-shared dilated graph attention for cortical surface parcellation [paper]
Siqi Liu, Hailiang Ye*, Bing Yang, Ming Li, Feilong Cao*
Medical & Biological Engineering & Computing, 2024, 62: 537–549.

A fast hypergraph neural network with detail preservation for hyperspectral image classification [paper]
Feilong Cao, Jieqin Bao, Bing Yang, Hailiang Ye*
International Journal of Remote Sensing, 2024, 45(9): 3104-3128.

Fast point completion network [paper] [code]
Chenghao Fang, Bing Yang, Hailiang Ye, Feilong Cao
Neural Computing and Applications, 2024, 54: 3135-3151.

Hierarchical structural graph neural network with local relation enhancement for hyperspectral image classification [paper]
Feilong Cao, Xiaomei Huang, Bing Yang, Hailiang Ye
Digital Signal Processing, 2024, 146: 104392.

A new self-augment CNN for 3D point cloud classification and segmentation [paper]
Xinhong Meng, Xinyu Lu, Hailiang Ye, Bing Yang, Feilong Cao
International Journal of Machine Learning and Cybernetics, 2024, 14:3765–3781.

GoLoG: Global-to-local decoupling graph network with joint optimization for hyperspectral image classification [paper]
Bing Yang, Hailiang Ye, Ming Li, Feilong Cao, Shirui Pan
IEEE Transactions on Geoscience and Remote Sensing, 2023, 61: 5528014.

A new deep graph attention approach with influence and preference relationship reconstruction for rate prediction recommendation [paper]
Hailiang Ye, Yuzhi Song, Ming Li, Feilong Cao
Information Processing & Management, 2023, 60: 103439.

Triplet teaching graph contrastive networks with self-evolving adaptive augmentation [paper] [code]
Jiaxing Miao, Feilong Cao, Ming Li, Bing Yang, Hailiang Ye
Pattern Recognition, 2023, 142: 109687.

Two-stream coupling network with bidirectional interaction between structure and texture for image inpainting [paper]
Xinru Shao, Hailiang Ye, Bing Yang, Feilong Cao
Expert Systems with Applications, 2023, 231: 120700.

Revisiting graph neural networks from hybrid regularized graph signal reconstruction [paper]
Jiaxing Miao, Feilong Cao, Hailiang Ye, Ming Li, Bing Yang
Neural Networks, 2023, 157: 444-459.

ICCL: Independent and correlative correspondence learning for few-shot image classification [paper]
Zijun Zheng, Heng Wu, Laishui Lv, Hailiang Ye, Changchun Zhang, Gaohang Yu
Knowledge-Based Systems, 2023, 266: 110412.

An iteration-based interactive attention network for 3D point cloud registration [paper]
Jiatong Shi, Hailiang Ye, Bing Yang, Feilong Cao
Neurocomputing, 2023, 560: 126822.

Multi-space and detail-supplemented attention network for point cloud completion [paper]
Min Xiang, Hailiang Ye, Bing Yang, Feilong Cao
Applied Intelligence, 2023, 53: 14971–14985.

A new method for two-stage partial-to-partial point cloud registration: Multi-level interaction perception [paper]
Xinhong Meng, Lei Zhu, Hailiang Ye, Feilong Cao
International Journal of Machine Learning and Cybernetics, 2023, 14:3765–3781.

Construction and approximation for a class of feedforward neural networks with sigmoidal function [paper]
Xinhong Meng, Jinyao Yan, Hailiang Ye, Feilong Cao
International Journal of Wavelets, Multiresolution and Information Processing, 2023, 21(6): 2350028.

A global-and-local feature fusion network for point cloud classification [paper]
Xinhong Meng, Meng Hu, Hailiang Ye, Ming Li, Feilong Cao
Proceedings of IEEE International Conference on Machine Learning and Cybernetics (ICMLC2023), 2023.7.9-7.11.

A novel method for hyperspectral image classification: Deep network with adaptive graph structure integration [paper]
Bing Yang, Feilong Cao, Hailiang Ye*
IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5523512.

Feature-grouped network with spectral-spatial connected attention for hyperspectral image classification [paper] ESI Highly Cited Paper 🏆
Wenhui Guo, Hailiang Ye, Feilong Cao
IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5500413.

A novel method for point cloud completion: Adaptive region shape fusion network [paper]
Hangkun Wang, Hailiang Ye, Bing Yang, Feilong Cao
Knowledge-Based Systems, 2022, 255: 109770.

Decouple the object: component-level semantic recognizer for point clouds classification [paper]
Rui Hu, Bing Yang, Hailiang Ye, Feilong Cao
Knowledge-Based Systems, 2022, 248: 108887.

Deep multi-graph neural networks with attention fusion for recommendation [paper]
Yuzhi Song, Hailiang Ye, Ming Li, Feilong Cao
Expert Systems with Applications, 2022, 191: 116240.

A novel multi-discriminator deep network for image segmentation [paper]
Yi Wang, Hailiang Ye, Feilong Cao
Applied Intelligence, 2022, 52: 1092-1109.

A novel method for image segmentation: Two-stage decoding network with boundary attention [paper]
Feilong Cao, Chengling Gao, Hailiang Ye
International Journal of Machine Learning and Cybernetics, 2022, 13: 1461–1473.

A universal rank approximation method for matrix completion [paper]
Jinyao Yan, Xinhong Meng, Feilong Cao, Hailiang Ye*
International Journal of Wavelets Multiresolution and Information Processing, 2022, 20(5): 2250016.

Adaptive deep cascade broad learning system and its application in image denoising [paper]
Hailiang Ye, Hong Li, C. L. Philip Chen
IEEE Transactions on Cybernetics, 2021, 51(9): 4450-4463.

A novel meta-learning framework: Multi-features adaptive aggregation method with information enhancer [paper]
Hailiang Ye, Yi Wang, Feilong Cao
Neural Networks, 2021, 144: 755-765.

3D mixed CNNs with edge-point feature learning [paper]
Zijin Du, Hailiang Ye, Feilong Cao
Knowledge-Based Systems, 2021, 221: 106985.

Multiscale fused network with additive channel-spatial attention for image segmentation [paper]
Chengling Gao, Hailiang Ye, Feilong Cao, Chenglin Wen, Qinghua Zhang, Feng Zhang
Knowledge-Based Systems, 2021, 214: 106754.

Convolutional neural networks with hybrid weights for 3D point cloud classification [paper]
Meng Hu, Hailiang Ye, Feilong Cao
Applied Intelligence, 2021, 51: 6983–6996.

A novel 3D shape classification algorithm: Point-to-vector capsule network [paper]
Hailiang Ye, Zijin Du, Feilong Cao
Neural Computing and Applications, 2021, 33: 16315-16328.

A hybrid regularization approach for random vector functional-link networks [paper]
Hailiang Ye, Feilong Cao, Dianhui Wang
Expert Systems with Applications , 2020, 140: 112912.

A hybrid truncated norm regularization method for matrix completion [paper]
Hailiang Ye, Hong Li, Feilong Cao, Liming Zhang
IEEE Transactions on Image Processing, 2019, 28(10): 5171-5186.

A novel rank approximation method for mixture noise removal of hyperspectral images [paper]
Hailiang Ye, Hong Li, Bing Yang, Feilong Cao, Yuanyan Tang
IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(7): 4457-4469.

Building feedforward neural networks with random weights for large scale datasets [paper]
Hailiang Ye, Feilong Cao, Dianhui Wang, Hong Li
Expert Systems with Applications , 2018, 106: 233-243.

Recovering low-rank and sparse matrix based on the truncated nuclear norm [paper]
Feilong Cao, Jiaying Chen, Hailiang Ye, Jianwei Zhao, Zhenghua Zhou
Neural Networks, 2017, 85: 10-20.

A probabilistic learning algorithm for robust modeling using neural networks with random weights [paper]
Feilong Cao, Hailiang Ye, Dianhui Wang
Expert Systems with Applications , 2015, 313: 62-78.