Multivariate Stancu operators defined on a simplex. - Ruyue Yang; Jingyi Xiong; Feilong Cao (Appl. Math. Comput., 2003)

The essential order of approximation for neural networks. - Zongben Xu; Feilong Cao (Sci. China Ser. F Inf. Sci., 2004)

Pointwise Approximation for Neural Networks. - Feilong Cao; Zongben Xu; Youmei Li (ISNN (1), 2005)

Generalization and Property Analysis of GENET. - Youmei Li; Zongben Xu; Feilong Cao (ISNN (1), 2005)

Derivatives of multidimensional Bernstein operators and smoothness. - Feilong Cao (J. Approx. Theory, 2005)

The Essential Approximation Order for Neural Networks with Trigonometric Hidden Layer Units. - Chunmei Ding; Feilong Cao; Zongben Xu (ISNN (1), 2006)

The Constructive Methods and Numerical Results for Approximation of Neural Networks. - Ruyue Yang; Xing Pan; Feilong Cao (ICNC (1), 2007)

An Improvement to Ant Colony Optimization Heuristic. - Youmei Li; Zongben Xu; Feilong Cao (ISNN (1), 2008)

The estimate for approximation error of neural networks: A constructive approach. - Feilong Cao; Tingfan Xie; Zongben Xu (Neurocomputing, 2008)

K-functionals and multivariate Bernstein polynomials. - Chunmei Ding; Feilong Cao (J. Approx. Theory, 2008)

Convergence rates for a class of neural networks with logarithmic function. - Feilong Cao; Yubo Yuan 001 (GrC, 2009)

Segmentation of Blood and Bone Marrow Cell Images via Learning by Sampling. - Chen Pan; Huijuan Lu; Feilong Cao (ICIC (1), 2009)

Marrow Cell Segmentation by Simulating Visual System. - Chen Pan; Feilong Cao (ICNC (1), 2009)

Face Image Recognition Combining Holistic and Local Features. - Chen Pan; Feilong Cao (ISNN (3), 2009)

Lower estimation of approximation rate for neural networks. - Feilong Cao; Yongquan Zhang; Zongben Xu (Sci. China Ser. F Inf. Sci., 2009)

The approximation operators with sigmoidal functions. - Zhixiang Chen 004; Feilong Cao (Comput. Math. Appl., 2009)

The errors of approximation for feedforward neural networks in the Lp metric. - Feilong Cao; Rui Zhang (Math. Comput. Model., 2009)

Adaptive control of singular nonlinear systems with convex/concave parametrization. - Qingxiang Fang; Feilong Cao (ICARCV, 2010)

The construction and approximation for feedforword neural networks with fixed weights. - Feilong Cao; Tingfan Xie (ICMLC, 2010)

Approximation by approximate interpolation neural networks with single hidden layer. - Chunmei Ding; Yubo Yuan 001; Feilong Cao (ICMLC, 2010)

Approximate interpolation by a class of neural networks in Lebesgue metric. - Chunmei Ding; Yubo Yuan 001; Feilong Cao (ICMLC, 2010)

Estimate human gene family number by improved k-means clustering. - Dongmei Pu; Yubo Yuan 001; Feilong Cao (ICMLC, 2010)

Canonical duality solution to support vector machine. - Yubo Yuan 001; Feilong Cao (ICMLC, 2010)

Sixth order polynomial smoothing approximation solution to support vector machine. - Yubo Yuan 001; Dongmei Pu; Feilong Cao (ICMLC, 2010)

Exact and approximate interpolation for neural networks with single hidden layer. - Feilong Cao; Yubo Yuan 001; Chunmei Ding (ICNC, 2010)

A new solution method to support vector machine based on arc smoothing function. - Yubo Yuan 001; Feilong Cao (ICNC, 2010)

Neural networks for interpolation of functionals on a Hilbert space. - Jianwei Zhao 004; Feilong Cao (ICNC, 2010)

Global errors for approximate approximations with Gaussian kernels on compact intervals. - Zhixiang Chen 004; Feilong Cao (Appl. Math. Comput., 2010)

Approximation capability of interpolation neural networks. - Feilong Cao; Shaobo Lin; Zongben Xu (Neurocomputing, 2010)

The errors in simultaneous approximation by feed-forward neural networks. - Tingfan Xie; Feilong Cao (Neurocomputing, 2010)

Constructive approximate interpolation by neural networks in the metric space. - Feilong Cao; Shaobo Lin; Zongben Xu (Math. Comput. Model., 2010)

Baby formula classification based on forth order polynomial smoothing support vector machine. - Yubo Yuan 001; Jing Lu; Feilong Cao (ICMLC, 2011)

A novel software reliability model with the decrease-rate of removing errors. - Hou-Ying Zhu; Yubo Yuan 001; Feilong Cao; Bo Liu (ICMLC, 2011)

The Connected Domination and Tree Domination of P(n, k) for k = 1, 2, [n/2]. - Chengye Zhao; Yuansheng Yang; Linlin Sun; Feilong Cao (Ars Comb., 2011)

The errors of simultaneous approximation of multivariate functions by neural networks. - Tingfan Xie; Feilong Cao (Comput. Math. Appl., 2011)

Optimal rate of the regularized regression learning algorithm. - Yongquan Zhang; Feilong Cao; Zongben Xu (Int. J. Comput. Math., 2011)

A study on effectiveness of extreme learning machine. - Yuguang Wang 001; Feilong Cao; Yubo Yuan 001 (Neurocomputing, 2011)

Optimization approximation solution for regression problem based on extreme learning machine. - Yubo Yuan 001; Yuguang Wang 001; Feilong Cao (Neurocomputing, 2011)

Estimation of learning rate of least square algorithm via Jackson operator. - Yongquan Zhang; Feilong Cao; Zongben Xu (Neurocomputing, 2011)

Essential rate for approximation by spherical neural networks. - Shaobo Lin; Feilong Cao; Zongben Xu (Neural Networks, 2011)

The Diameter of Connected Domination Critical Graphs. - Chengye Zhao; Feilong Cao (Ars Comb., 2012)

Estimation of convergence rate for multi-regression learning algorithm. - Zongben Xu; Yongquan Zhang; Feilong Cao (Sci. China Inf. Sci., 2012)

Learning rates of support vector machine classifier for density level detection. - Feilong Cao; Xing Xing; Jianwei Zhao 004 (Neurocomputing, 2012)

A general radial quasi-interpolation operator on the sphere. - Shaobo Lin; Feilong Cao; Xiangyu Chang; Zongben Xu (J. Approx. Theory, 2012)

Error estimates of quasi-interpolation and its derivatives. - Zhixiang Chen 004; Feilong Cao; Jinjie Hu (J. Comput. Appl. Math., 2012)

Software reliability modeling with removed errors and compounded-decreased-rate. - Yubo Yuan 001; Hou-Ying Zhu; Bo Liu; Feilong Cao (Math. Comput. Model., 2012)

Learning rates of least-square regularized regression with strongly mixing observation. - Yongquan Zhang; Feilong Cao; Canwei Yan (Int. J. Mach. Learn. Cybern., 2012)

Analysis of convergence performance of neural networks ranking algorithm. - Yongquan Zhang; Feilong Cao (Neural Networks, 2012)

Learning Rates for Regularized Classifiers Using Trigonometric Polynomial Kernels. - Feilong Cao; Dan Wu; Joonwhoan Lee (Neural Process. Lett., 2012)

Generalized extreme learning machine acting on a metric space. - Jianwei Zhao 004; Dong Sun Park; Joonwhoan Lee; Feilong Cao (Soft Comput., 2012)

Face Recognition Based on Random Weights Network and Quasi Singular Value Decomposition. - Zhenghua Zhou; Jianwei Zhao 004; Feilong Cao (ICIC (3), 2013)

Fast Image Classification Algorithms Based on Random Weights Networks. - Feilong Cao; Jianwei Zhao 004; Bo Liu (ISNN (1), 2013)

A Reduction Algorithm for the Big Data in 3D Surface Reconstruction. - Jianwei Zhao 004; Yanqing Fu; Yuanpeng Tan; Feilong Cao (SMC, 2013)

Approximation by neural networks with scattered data. - Shaobo Lin; Xiaofei Guo; Feilong Cao; Zongben Xu (Appl. Math. Comput., 2013)

Image classification based on effective extreme learning machine. - Feilong Cao; Bo Liu; Dong Sun Park (Neurocomputing, 2013)

Diagnosis of fatigue crack growth with recursive random weight networks. - Zhenghua Zhou; Jianwei Zhao 004; Feilong Cao (Comput. Electr. Eng., 2014)

Sparse algorithms of Random Weight Networks and applications. - Feilong Cao; Yuanpeng Tan; MiaoMiao Cai (Expert Syst. Appl., 2014)

Extended feed forward neural networks with random weights for face recognition. - Jing Lu; Jianwei Zhao 004; Feilong Cao (Neurocomputing, 2014)

A novel approach for fault diagnosis of induction motor with invariant character vectors. - Zhenghua Zhou; Jianwei Zhao 004; Feilong Cao (Inf. Sci., 2014)

Human face recognition based on ensemble of polyharmonic extreme learning machine. - Jianwei Zhao 004; Zhenghua Zhou; Feilong Cao (Neural Comput. Appl., 2014)

Compressed classification learning with Markov chain samples. - Feilong Cao; Tenghui Dai; Yongquan Zhang; Yuanpeng Tan (Neural Networks, 2014)

Generalization Bounds of Regularization Algorithm with Gaussian Kernels. - Feilong Cao; Yufang Liu; Weiguo Zhang (Neural Process. Lett., 2014)

Extreme learning machine with errors in variables. - Jianwei Zhao 004; Zhihui Wang 003; Feilong Cao (World Wide Web, 2014)

Leukocyte image segmentation using feed forward neural networks with random weights. - Feilong Cao; Jing Lu; Jianjun Chu; Zhenghua Zhou; Jianwei Zhao 004; Guoqiang Chen (ICNC, 2015)

Approximation by network operators with logistic activation functions. - Zhixiang Chen 004; Feilong Cao; Jinjie Hu (Appl. Math. Comput., 2015)

Multiscale interpolation on the sphere: Convergence rate and inverse theorem. - Ming Li 039; Feilong Cao (Appl. Math. Comput., 2015)

A novel algorithm of extended neural networks for image recognition. - Kankan Dai; Jianwei Zhao 004; Feilong Cao (Eng. Appl. Artif. Intell., 2015)

A novel face recognition method: Using random weight networks and quasi-singular value decomposition. - Wanggen Wan; Zhenghua Zhou; Jianwei Zhao 004; Feilong Cao (Neurocomputing, 2015)

A New System of Face Recognition: Using Fuzziness and Sparsity. - Yuanpeng Tan; Feilong Cao; MiaoMiao Cai (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2015)

Quantum artificial neural networks with applications. - Huaixin Cao; Feilong Cao; Dianhui Wang (Inf. Sci., 2015)

An adiabatic quantum algorithm and its application to DNA motif model discovery. - Huaixin Cao; Dianhui Wang; Feilong Cao (Inf. Sci., 2015)

A probabilistic learning algorithm for robust modeling using neural networks with random weights. - Feilong Cao; Hailiang Ye; Dianhui Wang 001 (Inf. Sci., 2015)

Learning Algorithm of Neural Networks on Spherical Cap. - Zhixiang Chen 004; Jinjie Hu; Feilong Cao (J. Networks, 2015)

A novel decorrelated neural network ensemble algorithm for face recognition. - Kankan Dai; Jianwei Zhao 004; Feilong Cao (Knowl. Based Syst., 2015)

A local learning algorithm for random weights networks. - Jianwei Zhao 004; Zhihui Wang 003; Feilong Cao; Dianhui Wang (Knowl. Based Syst., 2015)

Image Interpolation via Low-Rank Matrix Completion and Recovery. - Feilong Cao; MiaoMiao Cai; Yuanpeng Tan (IEEE Trans. Circuits Syst. Video Technol., 2015)

Scattered data approximation by neural networks operators. - Zhixiang Chen 004; Feilong Cao (Neurocomputing, 2016)

Simultaneous approximation by spherical neural networks. - Shaobo Lin; Feilong Cao (Neurocomputing, 2016)

An iterative learning algorithm for feedforward neural networks with random weights. - Feilong Cao; Dianhui Wang 001; Hou-Ying Zhu; Yuguang Wang 001 (Inf. Sci., 2016)

Pose and illumination variable face recognition via sparse representation and illumination dictionary. - Feilong Cao; Heping Hu; Jing Lu; Jianwei Zhao 004; Zhenghua Zhou; Jiao Wu (Knowl. Based Syst., 2016)

Image Super-Resolution via Adaptive ℓp (0<p<1) Regularization and Sparse Representation. - Feilong Cao; MiaoMiao Cai; Yuanpeng Tan; Jianwei Zhao 004 (IEEE Trans. Neural Networks Learn. Syst., 2016)

Consensus-based Parallel Algorithm for Robust Convex Optimization with Scenario Approach in Colored Network. - Fan Feng; Feilong Cao (IDEAL, 2017)

Super-resolution reconstruction: using non-local structure similarity and edge sharpness dictionary. - Jianwei Zhao 004; Heping Hu; Zhenghua Zhou; Feilong Cao (IET Image Process., 2017)

Sparse representation for robust face recognition by dictionary decomposition. - Feilong Cao; Xinshan Feng; Jianwei Zhao 004 (J. Vis. Commun. Image Represent., 2017)

Image super-resolution via adaptive sparse representation. - Jianwei Zhao 004; Heping Hu; Feilong Cao (Knowl. Based Syst., 2017)

Automatic detection and classification of leukocytes using convolutional neural networks. - Jianwei Zhao 004; Minshu Zhang; Zhenghua Zhou; Jianjun Chu; Feilong Cao (Medical Biol. Eng. Comput., 2017)

A novel segmentation algorithm for nucleus in white blood cells based on low-rank representation. - Feilong Cao; MiaoMiao Cai; Jianjun Chu; Jianwei Zhao 004; Zhenghua Zhou (Neural Comput. Appl., 2017)

Recovering low-rank and sparse matrix based on the truncated nuclear norm. - Feilong Cao; Jiaying Chen; Hailiang Ye; Jianwei Zhao 004; Zhenghua Zhou (Neural Networks, 2017)

A novel deep learning algorithm for incomplete face recognition: Low-rank-recovery network. - Jianwei Zhao 004; Yongbiao Lv; Zhenghua Zhou; Feilong Cao (Neural Networks, 2017)

Nonlocaly Multi-Morphological Representation for Image Reconstruction From Compressive Measurements. - Jiao Wu; Feilong Cao; Juncheng Yin (IEEE Trans. Image Process., 2017)

Segmentation of White Blood Cells Image Using Adaptive Location and Iteration. - Yuehua Liu; Feilong Cao; Jianwei Zhao 004; Jianjun Chu (IEEE J. Biomed. Health Informatics, 2017)

Building feedforward neural networks with random weights for large scale datasets. - Hailiang Ye; Feilong Cao; Dianhui Wang 001; Hong Li 009 (Expert Syst. Appl., 2018)

Image super-resolution via adaptive sparse representation and self-learning. - Jianwei Zhao 004; Tiantian Sun; Feilong Cao (IET Comput. Vis., 2018)

Efficient saliency detection using convolutional neural networks with feature selection. - Feilong Cao; Yuehua Liu; Dianhui Wang 001 (Inf. Sci., 2018)

多层前向人工神经网络图像分类算法 (Algorithm of Multi-layer Forward Artificial Neural Network for Image Classification). - Zhebin Gu; Feilong Cao (计算机科学, 2018)

A new method for image super-resolution with multi-channel constraints. - Feilong Cao; Keqiuyin Li (Knowl. Based Syst., 2018)

Robust object tracking using a sparse coadjutant observation model. - Jianwei Zhao 004; Weidong Zhang; Feilong Cao (Multim. Tools Appl., 2018)

Distributed support vector machine in master-slave mode. - Qingguo Chen; Feilong Cao (Neural Networks, 2018)

Sparsity-Based Spatiotemporal Fusion via Adaptive Multi-Band Constraints. - Hanchi Ying; Yee Leung; Feilong Cao; Tung Fung; Jie Xue 002 (Remote. Sens., 2018)

Single image super-resolution via multi-scale residual channel attention network. - Feilong Cao; Huan Liu (Neurocomputing, 2019)

Single image super-resolution based on adaptive convolutional sparse coding and convolutional neural networks. - Jianwei Zhao 004; Chen Chen; Zhenghua Zhou; Feilong Cao (J. Vis. Commun. Image Represent., 2019)

New architecture of deep recursive convolution networks for super-resolution. - Feilong Cao; Baijie Chen (Knowl. Based Syst., 2019)

Adaptive algorithms for low-rank and sparse matrix recovery with truncated nuclear norm. - Wenchao Qian; Feilong Cao (Int. J. Mach. Learn. Cybern., 2019)

Effective segmentations in white blood cell images using ϵ -SVR-based detection method. - Feilong Cao; Yuehua Liu; Zhen Huang; Jianjun Chu; Jianwei Zhao 004 (Neural Comput. Appl., 2019)

Super-resolution using neighbourhood regression with local structure prior. - Keqiuyin Li; Feilong Cao (Signal Process. Image Commun., 2019)

A Novel Rank Approximation Method for Mixture Noise Removal of Hyperspectral Images. - Hailiang Ye; Hong Li 009; Bing Yang; Feilong Cao; Yuanyan Tang (IEEE Trans. Geosci. Remote. Sens., 2019)

A Hybrid Truncated Norm Regularization Method for Matrix Completion. - Hailiang Ye; Hong Li 009; Feilong Cao; Liming Zhang 002 (IEEE Trans. Image Process., 2019)

On the Approximation Lower Bound for Neural Nets with Random Weights. - Sho Sonoda; Ming Li 065; Feilong Cao; Changqin Huang; Yu Guang Wang 001 (CoRR, 2020)

A hybrid regularization approach for random vector functional-link networks. - Hailiang Ye; Feilong Cao; Dianhui Wang 001 (Expert Syst. Appl., 2020)

Adaptive sparse and dense hybrid representation with nonconvex optimization. - Xuejun Wang; Feilong Cao; Wenjian Wang (Frontiers Comput. Sci., 2020)

Deep hybrid dilated residual networks for hyperspectral image classification. - Feilong Cao; Wenhui Guo (Neurocomputing, 2020)

A Compact Recursive Dense Convolutional Network for image classification. - Jianwei Zhao 004; Taoye Huang; Zhenghua Zhou; Feilong Cao (Neurocomputing, 2020)

Modeling a stochastic age-structured capital system with Poisson jumps using neural networks. - Jie Ren; Qimin Zhang; Feilong Cao; Chunmei Ding; Li Wang (Inf. Sci., 2020)

Cascaded dual-scale crossover network for hyperspectral image classification. - Feilong Cao; Wenhui Guo (Knowl. Based Syst., 2020)

Lightweight multi-scale residual networks with attention for image super-resolution. - Huan Liu; Feilong Cao; Chenglin Wen; Qinghua Zhang (Knowl. Based Syst., 2020)

Deconvolutional neural network for image super-resolution. - Feilong Cao; Kaixuan Yao; Jiye Liang (Neural Networks, 2020)

Improved dual-scale residual network for image super-resolution. - Huan Liu; Feilong Cao (Neural Networks, 2020)

Convolutional neural networks with hybrid weights for 3D point cloud classification. - Meng Hu; Hailiang Ye; Feilong Cao (Appl. Intell., 2021)

Consensus-based distributed learning for robust convex optimization with a scenario approach. - Feilong Cao; Fan Feng (Concurr. Comput. Pract. Exp., 2021)

Densely connected network with improved pyramidal bottleneck residual units for super-resolution. - Feilong Cao; Baijie Chen (J. Vis. Commun. Image Represent., 2021)

3D mixed CNNs with edge-point feature learning. - Zijin Du; Hailiang Ye; Feilong Cao (Knowl. Based Syst., 2021)

Multiscale fused network with additive channel-spatial attention for image segmentation. - Chengling Gao; Hailiang Ye; Feilong Cao; Chenglin Wen; Qinghua Zhang; Feng Zhang (Knowl. Based Syst., 2021)

A stochastic age-structured HIV/AIDS model based on parameters estimation and its numerical calculation. - Jie Ren; Qimin Zhang; Xining Li; Feilong Cao; Ming Ye (Math. Comput. Simul., 2021)

Algorithms of matrix recovery based on truncated Schatten p-norm. - Chenglin Wen; Wenchao Qian; Qinghua Zhang; Feilong Cao (Int. J. Mach. Learn. Cybern., 2021)

An automatic 2D to 3D video conversion approach based on RGB-D images. - Baiyu Pan; Liming Zhang 002; Hanxiong Yin; Jun Lan; Feilong Cao (Multim. Tools Appl., 2021)

A novel 3D shape classification algorithm: point-to-vector capsule network. - Hailiang Ye; Zijin Du; Feilong Cao (Neural Comput. Appl., 2021)

A novel meta-learning framework: Multi-features adaptive aggregation method with information enhancer. - Hailiang Ye; Yi Wang; Feilong Cao (Neural Networks, 2021)

Deep neural network compression through interpretability-based filter pruning. - Kaixuan Yao; Feilong Cao; Yee Leung; Jiye Liang (Pattern Recognit., 2021)

Salient Object Detection Based on Visual Perceptual Saturation and Two-Stream Hybrid Networks. - Chen Pan; Jianfeng Liu; Wei Qi Yan 001; Feilong Cao; Wei He; Yongxia Zhou (IEEE Trans. Image Process., 2021)

Multi-view graph convolutional networks with attention mechanism. - Kaixuan Yao; Jiye Liang; Jianqing Liang; Ming Li 065; Feilong Cao (Artif. Intell., 2022)

A novel multi-discriminator deep network for image segmentation. - Yi Wang; Hailiang Ye; Feilong Cao (Appl. Intell., 2022)

Deep multi-graph neural networks with attention fusion for recommendation. - Yuzhi Song; Hailiang Ye; Ming Li 065; Feilong Cao (Expert Syst. Appl., 2022)

A universal rank approximation method for matrix completion. - Jinyao Yan; Xinhong Meng; Feilong Cao; Hailiang Ye (Int. J. Wavelets Multiresolution Inf. Process., 2022)

Decouple the object: Component-level semantic recognizer for point clouds classification. - Rui Hu; Bing Yang; Hailiang Ye; Feilong Cao; Chenglin Wen; Qinghua Zhang (Knowl. Based Syst., 2022)

A novel method for point cloud completion: Adaptive region shape fusion network. - Hangkun Wang; Hailiang Ye; Bing Yang; Feilong Cao (Knowl. Based Syst., 2022)

A novel method for image segmentation: two-stage decoding network with boundary attention. - Feilong Cao; Chengling Gao; Hailiang Ye (Int. J. Mach. Learn. Cybern., 2022)

A new rotation forest ensemble algorithm. - Chenglin Wen; Tingting Huai; Qinghua Zhang; Zhihuan Song; Feilong Cao (Int. J. Mach. Learn. Cybern., 2022)

Feature-Grouped Network With Spectral-Spatial Connected Attention for Hyperspectral Image Classification. - Wenhui Guo; Hailiang Ye; Feilong Cao (IEEE Trans. Geosci. Remote. Sens., 2022)

A Novel Method for Hyperspectral Image Classification: Deep Network With Adaptive Graph Structure Integration. - Bing Yang; Feilong Cao; Hailiang Ye (IEEE Trans. Geosci. Remote. Sens., 2022)

How Powerful are Shallow Neural Networks with Bandlimited Random Weights? - Ming Li 065; Sho Sonoda; Feilong Cao; Yu Guang Wang 001; Jiye Liang (ICML, 2023)

A Global-and-Local Feature Fusion Network for Point Cloud Classification. - Xinhong Meng; Meng Hu; Hailiang Ye; Ming Li 065; Feilong Cao (ICMLC, 2023)

Construction and approximation for a class of feedforward neural networks with sigmoidal function. - Xinhong Meng; Jinyao Yan; Hailiang Ye; Feilong Cao (Int. J. Wavelets Multiresolution Inf. Process., 2023)

Revisiting graph neural networks from hybrid regularized graph signal reconstruction. - Jiaxing Miao; Feilong Cao; Hailiang Ye; Ming Li 065; Bing Yang (Neural Networks, 2023)

GoLoG: Global-to-Local Decoupling Graph Network With Joint Optimization for Hyperspectral Image Classification. - Bing Yang; Hailiang Ye; Ming Li 065; Feilong Cao; Shirui Pan (IEEE Trans. Geosci. Remote. Sens., 2023)

Are Graph Convolutional Networks With Random Weights Feasible? - Changqin Huang; Ming Li 065; Feilong Cao; Hamido Fujita; Zhao Li 007; Xindong Wu 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

A dynamic graph aggregation framework for 3D point cloud registration. - Feilong Cao; Jiatong Shi; Chenglin Wen (Eng. Appl. Artif. Intell., 2023)

Image Super-Resolution Using a Simple Transformer Without Pretraining. - Huan Liu 012; Mingwen Shao; Chao Wang 102; Feilong Cao (Neural Process. Lett., 2023)

Multi-space and detail-supplemented attention network for point cloud completion. - Min Xiang; Hailiang Ye; Bing Yang; Feilong Cao (Appl. Intell., 2023)

A new deep graph attention approach with influence and preference relationship reconstruction for rate prediction recommendation. - Hailiang Ye; Yuzhi Song; Ming Li 065; Feilong Cao (Inf. Process. Manag., 2023)

Adaptive one-stage generative adversarial network for unpaired image super-resolution. - Mingwen Shao; Huan Liu 012; Jianxin Yang; Feilong Cao (Neural Comput. Appl., 2023)

Triplet teaching graph contrastive networks with self-evolving adaptive augmentation. - Jiaxing Miao; Feilong Cao; Ming Li 065; Bing Yang; Hailiang Ye (Pattern Recognit., 2023)

Two-stream coupling network with bidirectional interaction between structure and texture for image inpainting. - Xinru Shao; Hailiang Ye; Bing Yang; Feilong Cao (Expert Syst. Appl., 2023)

A new method for two-stage partial-to-partial 3D point cloud registration: multi-level interaction perception. - Xinhong Meng; Lei Zhu; Hailiang Ye; Feilong Cao (Int. J. Mach. Learn. Cybern., 2023)

An iteration-based interactive attention network for 3D point cloud registration. - Jiatong Shi; Hailiang Ye; Bing Yang; Feilong Cao (Neurocomputing, 2023)

Long and Short-Range Dependency Graph Structure Learning Framework on Point Cloud. - Jiye Liang; Zijin Du; Jianqing Liang; Kaixuan Yao; Feilong Cao (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Two-view point cloud registration network: feature and geometry. - Lingpeng Wang; Bing Yang; Hailiang Ye; Feilong Cao (Appl. Intell., 2024)

Component-based Sketching for Deep ReLU Nets. - Di Wang 008; Shao-Bo Lin; Deyu Meng; Feilong Cao (CoRR, 2024)

Hierarchical structural graph neural network with local relation enhancement for hyperspectral image classification. - Feilong Cao; Xiaomei Huang; Bing Yang; Hailiang Ye (Digit. Signal Process., 2024)

A novel Complementary Dual-aware Network for point cloud classification. - Rui Hu; Feilong Cao; Wenjian Wang (Eng. Appl. Artif. Intell., 2024)

An effective targeted label adversarial attack on graph neural networks by strategically allocating the attack budget. - Feilong Cao; Qiyang Chen; Hailiang Ye (Knowl. Based Syst., 2024)

A new method for point cloud registration: Adaptive relation-oriented convolution and recurrent correspondence-walk. - Feilong Cao; Lei Zhu; Hailiang Ye; Chenglin Wen; Qinghua Zhang (Knowl. Based Syst., 2024)

Fast point completion network. - Chenghao Fang; Bing Yang; Hailiang Ye; Feilong Cao (Neural Comput. Appl., 2024)

Node-personalized multi-graph convolutional networks for recommendation. - Tiantian Zhou; Hailiang Ye; Feilong Cao (Neural Networks, 2024)

A New Strategy of Graph Structure Attack: Multi-View Perturbation Candidate Edge Learning. - Feilong Cao; Qiyang Chen; Hailiang Ye (IEEE Trans. Netw. Sci. Eng., 2024)

A joint parcellation and boundary network with multi-rate-shared dilated graph attention for cortical surface parcellation. - Siqi Liu; Hailiang Ye; Bing Yang; Ming Li 065; Feilong Cao (Medical Biol. Eng. Comput., 2024)

A new self-augment CNN for 3D point cloud classification and segmentation. - Xinhong Meng; Xinyu Lu; Hailiang Ye; Bing Yang; Feilong Cao (Int. J. Mach. Learn. Cybern., 2024)

A novel autism spectrum disorder identification method: spectral graph network with brain-population graph structure joint learning. - Sihui Li; Duo Li; Rui Zhang 005; Feilong Cao (Int. J. Mach. Learn. Cybern., 2024)

A Novel Local-Global Graph Convolutional Method for Point Cloud Semantic Segmentation. - Zijin Du; Hailiang Ye; Feilong Cao (IEEE Trans. Neural Networks Learn. Syst., 2024)

Label-Decoupled Medical Image Segmentation With Spatial-Channel Graph Convolution and Dual Attention Enhancement. - Qingting Jiang; Hailiang Ye; Bing Yang; Feilong Cao (IEEE J. Biomed. Health Informatics, 2024)

A new matrix representation for the Heisenberg group. - Qiuhui Chen; Feilong Cao (Int. J. Wavelets Multiresolution Inf. Process., 2024)

SharpGConv: A Novel Graph Method With Plug-and-Play Sharpening Convolution for Point Cloud Registration. - Feilong Cao; Lingpeng Wang; Hailiang Ye (IEEE Trans. Circuits Syst. Video Technol., 2024)

Robust graph neural networks with Dirichlet regularization and residual connection. - Kaixuan Yao; Zijin Du; Ming Li 065; Feilong Cao; Jiye Liang (Int. J. Mach. Learn. Cybern., 2024)

Graph Regulation Network for Point Cloud Segmentation. - Zijin Du; Jianqing Liang; Jiye Liang; Kaixuan Yao; Feilong Cao (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

A Multi-View Graph Contrastive Learning Framework for Defending Against Adversarial Attacks. - Feilong Cao; Xing Ye; Hailiang Ye (IEEE Trans. Emerg. Top. Comput. Intell., 2024)

An enhanced network with parallel graph node diffusion and node similarity contrastive loss for hyperspectral image classification. - Hailiang Ye; Xiaomei Huang; Houying Zhu; Feilong Cao (Digit. Signal Process., 2025)

Construction and approximation rate for feedforward neural network operators with sigmoidal functions. - Dansheng Yu; Feilong Cao (J. Comput. Appl. Math., 2025)

TSI-GCN: Translation and scaling invariant GCN for 3D point cloud analysis. - Zijin Du; Jiye Liang; Kaixuan Yao; Feilong Cao (Pattern Recognit. Lett., 2025)

An adaptive contextual learning network for image inpainting. - Feilong Cao; Xinru Shao; Rui Zhang; Chenglin Wen (Signal Process. Image Commun., 2025)

A Joint Multiscale Graph Attention and Classify-Driven Autoencoder Framework for Hyperspectral Unmixing. - Feilong Cao; Yujia Situ; Hailiang Ye (IEEE Trans. Geosci. Remote. Sens., 2025)

Feature Qualification by Deep Nets: A Constructive Approach. - Feilong Cao; Shao-Bo Lin (CoRR, 2025)

Semantic-spatial feature-fused cortical surface parcellation: a scale-unified spatial learning network with boundary contrastive loss. - Hailiang Ye; Siqi Liu; Ming Li 065; Houying Zhu; Feilong Cao (Medical Biol. Eng. Comput., 2025)