CDA-LSTM: an evolutionary convolution-based dual-attention LSTM for univariate time series prediction. - Xiaoquan Chu; Haibin Jin; Yue Li; Jianying Feng; Weisong Mu (Neural Comput. Appl., 2021)

GrapeGAN: Unsupervised image enhancement for improved grape leaf disease recognition. - Haibin Jin; Yue Li; Jianfang Qi; Jianying Feng; Dong Tian; Weisong Mu (Comput. Electron. Agric., 2022)

A new oversampling method and improved radial basis function classifier for customer consumption behavior prediction. - Yue Li; Xiaoyun Jia; Ruili Wang; Jianfang Qi; Haibin Jin; Xiaoquan Chu; Weisong Mu (Expert Syst. Appl., 2022)

CWAN: Self-supervised learning for deep grape disease image composition. - Haibin Jin; Xiaoquan Chu; Jianfang Qi; Xinxin Zhang; Weisong Mu (Eng. Appl. Artif. Intell., 2023)

User value identification based on an improved consumer value segmentation algorithm. - Jianfang Qi; Yue Li; Haibin Jin; Jianying Feng; Weisong Mu (Kybernetes, 2023)

Local Reversible Transformer for semantic segmentation of grape leaf diseases. - Xinxin Zhang; Fei Li 022; Haibin Jin; Weisong Mu (Appl. Soft Comput., 2023)

A novel stratification clustering algorithm based on a new local density estimation method and an improved local inter-cluster distance measure. - Jianfang Qi; Yue Li; Haibin Jin; Jianying Feng; Dong Tian; Weisong Mu (Int. J. Mach. Learn. Cybern., 2023)

An Improved Genetic-XGBoost Classifier for Customer Consumption Behavior Prediction. - Yue Li; Jianfang Qi; Haibin Jin; Dong Tian; Weisong Mu; Jianying Feng (Comput. J., 2024)

Learning multiple attention transformer super-resolution method for grape disease recognition. - Haibin Jin; Xiaoquan Chu; Jianfang Qi; Jianying Feng; Weisong Mu (Expert Syst. Appl., 2024)