Robust Joint Representation of Intrinsic Mean and Kernel Function of Lie Group for Remote Sensing Scene Classification. - Chengjun Xu; Guobin Zhu; Jingqian Shu (IEEE Geosci. Remote. Sens. Lett., 2021)

A Lightweight Intrinsic Mean for Remote Sensing Classification With Lie Group Kernel Function. - Chengjun Xu; Guobin Zhu; Jingqian Shu (IEEE Geosci. Remote. Sens. Lett., 2021)

Educational Data Mining: Dropout Prediction in XuetangX MOOCs. - Chengjun Xu; Guobin Zhu; Jian Ye; Jingqian Shu (Neural Process. Lett., 2022)

A Combination of Lie Group Machine Learning and Deep Learning for Remote Sensing Scene Classification Using Multi-Layer Heterogeneous Feature Extraction and Fusion. - Chengjun Xu; Guobin Zhu; Jingqian Shu (Remote. Sens., 2022)

A Lightweight and Robust Lie Group-Convolutional Neural Networks Joint Representation for Remote Sensing Scene Classification. - Chengjun Xu; Guobin Zhu; Jingqian Shu (IEEE Trans. Geosci. Remote. Sens., 2022)

Scene Classification Based on Heterogeneous Features of Multi-Source Data. - Chengjun Xu; Jingqian Shu; Guobin Zhu (Remote. Sens., 2023)

Adversarial Remote Sensing Scene Classification Based on Lie Group Feature Learning. - Chengjun Xu; Jingqian Shu; Guobin Zhu (Remote. Sens., 2023)

Multi-Feature Dynamic Fusion Cross-Domain Scene Classification Model Based on Lie Group Space. - Chengjun Xu; Jingqian Shu; Guobin Zhu (Remote. Sens., 2023)

A Scene Classification Model Based on Global-Local Features and Attention in Lie Group Space. - Chengjun Xu; Jingqian Shu; Zhenghan Wang; Jialin Wang (Remote. Sens., 2024)