Object Detection in Remote Sensing Images Based on Improved Bounding Box Regression and Multi-Level Features Fusion. - Xiaoliang Qian; Sheng Lin 005; Gong Cheng 003; Xiwen Yao; Hangli Ren; Wei Wang 245 (Remote. Sens., 2020)

Multiscale Superpixel Guided Discriminative Forest for Hyperspectral Anomaly Detection. - Xi Cheng; Min Zhang 015; Sheng Lin 005; Kexue Zhou; Liang Wang; Hai Wang 015 (Remote. Sens., 2022)

Hyperspectral Anomaly Detection via Dual Dictionaries Construction Guided by Two-Stage Complementary Decision. - Sheng Lin 005; Min Zhang 015; Xi Cheng; Liang Wang; Maiping Xu; Hai Wang 015 (Remote. Sens., 2022)

Two-Stream Isolation Forest Based on Deep Features for Hyperspectral Anomaly Detection. - Xi Cheng; Min Zhang 015; Sheng Lin 005; Kexue Zhou; Shaobo Zhao; Hai Wang 015 (IEEE Geosci. Remote. Sens. Lett., 2023)

Hyperspectral Anomaly Detection via Sparse Representation and Collaborative Representation. - Sheng Lin 005; Min Zhang 015; Xi Cheng; Kexue Zhou; Shaobo Zhao; Hai Wang 015 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023)

Dual Collaborative Constraints Regularized Low-Rank and Sparse Representation via Robust Dictionaries Construction for Hyperspectral Anomaly Detection. - Sheng Lin 005; Min Zhang 015; Xi Cheng; Kexue Zhou; Shaobo Zhao; Hai Wang 015 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023)

Arbitrary-Oriented Ellipse Detector for Ship Detection in Remote Sensing Images. - Kexue Zhou; Min Zhang 015; Honghui Zhao; Rui Tang; Sheng Lin 005; Xi Cheng; Hai Wang 015 (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023)

A combination network of CNN and transformer for interference identification. - Hu Zhang; Meng Zhao; Min Zhang 015; Sheng Lin 005; Youqiang Dong; Hai Wang 015 (Frontiers Comput. Neurosci., 2023)

Hyperspectral Anomaly Detection Using Spatial-Spectral-Based Union Dictionary and Improved Saliency Weight. - Sheng Lin 005; Min Zhang 015; Xi Cheng; Shaobo Zhao; Lei Shi 023; Hai Wang 015 (Remote. Sens., 2023)

Memory-Augmented Autoencoder With Adaptive Reconstruction and Sample Attribution Mining for Hyperspectral Anomaly Detection. - Yu Huo; Xi Cheng; Sheng Lin 005; Min Zhang 015; Hai Wang 015 (IEEE Trans. Geosci. Remote. Sens., 2024)

Deep Feature Aggregation Network for Hyperspectral Anomaly Detection. - Xi Cheng; Yu Huo; Sheng Lin 005; Youqiang Dong; Shaobo Zhao; Min Zhang 015; Hai Wang 015 (IEEE Trans. Instrum. Meas., 2024)

Deep Self-Representation Learning Framework for Hyperspectral Anomaly Detection. - Xi Cheng; Min Zhang 015; Sheng Lin 005; Yunsong Li; Hai Wang 015 (IEEE Trans. Instrum. Meas., 2024)

Low-Rank and Sparse Representation Inspired Interpretable Network for Hyperspectral Anomaly Detection. - Sheng Lin 005; Xi Cheng; Yinfeng Zeng; Yu Huo; Min Zhang 015; Hai Wang 015 (IEEE Trans. Instrum. Meas., 2024)

Dynamic Low-Rank and Sparse Priors Constrained Deep Autoencoders for Hyperspectral Anomaly Detection. - Sheng Lin 005; Min Zhang 015; Xi Cheng; Lei Shi 023; Paolo Gamba; Hai Wang 015 (IEEE Trans. Instrum. Meas., 2024)

Hyperspectral Anomaly Detection via Low-Rank Representation with Dual Graph Regularizations and Adaptive Dictionary. - Xi Cheng; Ruiqi Mu; Sheng Lin 005; Min Zhang 015; Hai Wang 015 (Remote. Sens., 2024)

Modulation recognition method based on multimodal features. - Hu Zhang; Yin Kuang; Ronghui Huang; Sheng Lin 005; Youqiang Dong; Min Zhang 015 (Frontiers Commun. Networks, 2025)