Automatic road crack detection using random structured forests Y Shi, L Cui, Z Qi, F Meng, Z Chen IEEE Transactions on Intelligent Transportation Systems 17 (12), 3434-3445, 2016 | 1324 | 2016 |
A novel graph convolutional feature based convolutional neural network for stock trend prediction W Chen, M Jiang, WG Zhang, Z Chen Information Sciences 556, 67-94, 2021 | 247 | 2021 |
The two-stage machine learning ensemble models for stock price prediction by combining mode decomposition, extreme learning machine and improved harmony search algorithm M Jiang, L Jia, Z Chen, W Chen Annals of Operations Research, 1-33, 2022 | 94 | 2022 |
Pavement distress detection using random decision forests L Cui, Z Qi, Z Chen, F Meng, Y Shi Data Science: Second International Conference, ICDS 2015, Sydney, Australia …, 2015 | 84 | 2015 |
Ensemble learning with label proportions for bankruptcy prediction Z Chen, W Chen, Y Shi Expert Systems with Applications 146, 113155, 2020 | 83 | 2020 |
A survey on semantic segmentation B Li, Y Shi, Z Qi, Z Chen 2018 IEEE International Conference on Data Mining Workshops (ICDMW), 1233-1240, 2018 | 64 | 2018 |
A novel clustering-based image segmentation via density peaks algorithm with mid-level feature Y Shi, Z Chen, Z Qi, F Meng, L Cui Neural Computing and Applications 28, 29-39, 2017 | 64 | 2017 |
A novel method for time series prediction based on error decomposition and nonlinear combination of forecasters W Chen, H Xu, Z Chen, M Jiang Neurocomputing 426, 85-103, 2021 | 60 | 2021 |
Image segmentation via improving clustering algorithms with density and distance Z Chen, Z Qi, F Meng, L Cui, Y Shi Procedia Computer Science 55, 1015-1022, 2015 | 52 | 2015 |
Short-term stock trends prediction based on sentiment analysis and machine learning Y Qiu, Z Song, Z Chen Soft Computing 26 (5), 2209-2224, 2022 | 50 | 2022 |
Unsupervised feature selection by non-convex regularized self-representation J Miao, Y Ping, Z Chen, XB Jin, P Li, L Niu Expert Systems with Applications 173, 114643, 2021 | 35 | 2021 |
Learning with label proportions based on nonparallel support vector machines Z Chen, Z Qi, B Wang, L Cui, F Meng, Y Shi Knowledge-Based Systems 119, 126-141, 2017 | 34 | 2017 |
Predicting stock market crisis via market indicators and mixed frequency investor sentiments S Lu, C Liu, Z Chen Expert Systems with Applications 186, 115844, 2021 | 27 | 2021 |
Linear twin svm for learning from label proportions B Wang, Z Chen, Z Qi 2015 IEEE/WIC/ACM International Conference on Web Intelligence and …, 2015 | 21 | 2015 |
Integrated GCN-LSTM stock prices movement prediction based on knowledge-incorporated graphs construction Y Shi, Y Wang, Y Qu, Z Chen International Journal of Machine Learning and Cybernetics 15 (1), 161-176, 2024 | 17 | 2024 |
Learning from label proportions with pinball loss Y Shi, L Cui, Z Chen, Z Qi International Journal of Machine Learning and Cybernetics 10, 187-205, 2019 | 17 | 2019 |
Research on graph neural network in stock market W Zhang, Z Chen, J Miao, X Liu Procedia Computer Science 214, 786-792, 2022 | 14 | 2022 |
Constrained matrix factorization for semi-weakly learning with label proportions Z Chen, Y Shi, Z Qi Pattern Recognition 91, 13-24, 2019 | 14 | 2019 |
Review of graph construction and graph learning in stock price prediction Y Wang, Y Qu, Z Chen Procedia Computer Science 214, 771-778, 2022 | 13 | 2022 |
Improved credit risk prediction based on an integrated graph representation learning approach with graph transformation Y Shi, Y Qu, Z Chen, Y Mi, Y Wang European Journal of Operational Research 315 (2), 786-801, 2024 | 12 | 2024 |