Applying convolutional neural networks for detecting wheat stripe rust transmission centers under complex field conditions using RGB-based high spatial resolution images from UAVs. - Jie Deng 002; Huiru Zhou; Xuan Lv; Lujia Yang; Jiali Shang; Qiuyu Sun; Xin Zheng; Congying Zhou; Baoqiang Zhao; Jiachong Wu; Zhanhong Ma (Comput. Electron. Agric., 2022)

Assessing Macro Disease Index of Wheat Stripe Rust Based on Segformer with Complex Background in the Field. - Jie Deng 002; Xuan Lv; Lujia Yang; Baoqiang Zhao; Congying Zhou; Ziqian Yang; Jiarui Jiang; Ning Ning; Jinyu Zhang; Junzheng Shi; Zhanhong Ma (Sensors, 2022)

Quantitative Estimation of Wheat Stripe Rust Disease Index Using Unmanned Aerial Vehicle Hyperspectral Imagery and Innovative Vegetation Indices. - Jie Deng 002; Rui Wang; Lujia Yang; Xuan Lv; Ziqian Yang; Kai Zhang; Congying Zhou; Pengju Liu; Zhifang Wang; Ahsan Abdullah 001; Zhanhong Ma (IEEE Trans. Geosci. Remote. Sens., 2023)

Efficient Wheat Lodging Detection Using UAV Remote Sensing Images and an Innovative Multi-Branch Classification Framework. - Kai Zhang; Rundong Zhang; Ziqian Yang; Jie Deng 002; Ahsan Abdullah 001; Congying Zhou; Xuan Lv; Rui Wang; Zhanhong Ma (Remote. Sens., 2023)

Pixel-level regression for UAV hyperspectral images: Deep learning-based quantitative inverse of wheat stripe rust disease index. - Jie Deng 002; Xunhe Zhang; Ziqian Yang; Congying Zhou; Rui Wang; Kai Zhang; Xuan Lv; Lujia Yang; Zhifang Wang; Pengju Li; Zhanhong Ma (Comput. Electron. Agric., 2023)

Using UAV hyperspectral imagery and deep learning for Object-Based quantitative inversion of Zanthoxylum rust disease index. - Kai Zhang; Jie Deng 002; Congying Zhou; Jiangui Liu; Xuan Lv; Ying Wang; Enhong Sun; Yan Liu; Zhanhong Ma; Jiali Shang (Int. J. Appl. Earth Obs. Geoinformation, 2024)

RustQNet: Multimodal deep learning for quantitative inversion of wheat stripe rust disease index. - Jie Deng 002; Danfeng Hong; Chenyu Li 002; Jing Yao 002; Ziqian Yang; Zhijian Zhang; Jocelyn Chanussot (Comput. Electron. Agric., 2024)

A Survey of Sample-Efficient Deep Learning for Change Detection in Remote Sensing: Tasks, Strategies, and Challenges. - Lei Ding 008; Danfeng Hong; Maofan Zhao; Hongruixuan Chen; Chenyu Li 002; Jie Deng 002; Naoto Yokoya; Lorenzo Bruzzone; Jocelyn Chanussot (CoRR, 2025)

Joint Super-Resolution and Segmentation for 1-m Impervious Surface Area Mapping in China's Yangtze River Economic Belt. - Jie Deng 002; Danfeng Hong; Chenyu Li 002; Naoto Yokoya (CoRR, 2025)