Quantitative Identification of Maize Lodging-Causing Feature Factors Using Unmanned Aerial Vehicle Images and a Nomogram Computation. - Liang Han; Guijun Yang; Haikuan Feng; Chengquan Zhou; Hao Yang 009; Bo Xu 017; Zhenhai Li; Xiaodong Yang (Remote. Sens., 2018)

A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera. - Jibo Yue; Haikuan Feng; Xiuliang Jin; Huanhuan Yuan; Zhenhai Li; Chengquan Zhou; Guijun Yang; Qingjiu Tian (Remote. Sens., 2018)

Recognition of Wheat Spike from Field Based Phenotype Platform Using Multi-Sensor Fusion and Improved Maximum Entropy Segmentation Algorithms. - Chengquan Zhou; Dong Liang 011; Xiaodong Yang; Bo Xu 017; Guijun Yang (Remote. Sens., 2018)

Fusion of Unmanned Aerial Vehicle Panchromatic and Hyperspectral Images Combining Joint Skewness-Kurtosis Figures and a Non-Subsampled Contourlet Transform. - Jinling Zhao; Chengquan Zhou; Linsheng Huang; Xiaodong Yang; Bo Xu 017; Dong Liang 011 (Sensors, 2018)

An Integrated Skeleton Extraction and Pruning Method for Spatial Recognition of Maize Seedlings in MGV and UAV Remote Images. - Chengquan Zhou; Guijun Yang; Dong Liang 011; Xiaodong Yang; Bo Xu 017 (IEEE Trans. Geosci. Remote. Sens., 2018)

Combined Use of FCN and Harris Corner Detection for Counting Wheat Ears in Field Conditions. - Daoyong Wang; Yuanyuan Fu; Guijun Yang; Xiaodong Yang; Dong Liang 011; Chengquan Zhou; Ning Zhang; Hongya Wu; Dongyan Zhang 001 (IEEE Access, 2019)

A dynamic soil endmember spectrum selection approach for soil and crop residue linear spectral unmixing analysis. - Jibo Yue; Qingjiu Tian; Shaofei Tang; Kaijian Xu; Chengquan Zhou (Int. J. Appl. Earth Obs. Geoinformation, 2019)

Using Hyperspectral Crop Residue Angle Index to Estimate Maize and Winter-Wheat Residue Cover: A Laboratory Study. - Jibo Yue; Qingjiu Tian; Xinyu Dong; Kaijian Xu; Chengquan Zhou (Remote. Sens., 2019)

Automated Counting of Rice Panicle by Applying Deep Learning Model to Images from Unmanned Aerial Vehicle Platform. - Chengquan Zhou; Hongbao Ye; Jun Hu; Xiaoyan Shi; Shan Hua; Jibo Yue; Zhifu Xu; Guijun Yang (Sensors, 2019)

Recognizing black point in wheat kernels and determining its extent using multidimensional feature extraction and a naive Bayes classifier. - Chengquan Zhou; Guijun Yang; Dong Liang 011; Jun Hu; Hao Yang 009; Jibo Yue; Ruirui Yan; Liang Han; Linsheng Huang; Lijun Xu (Comput. Electron. Agric., 2021)

Real-time nondestructive fish behavior detecting in mixed polyculture system using deep-learning and low-cost devices. - Jun Hu; Dandan Zhao; Yanfeng Zhang; Chengquan Zhou; Wenxuan Chen (Expert Syst. Appl., 2021)

An automated, high-performance approach for detecting and characterizing broccoli based on UAV remote-sensing and transformers: A case study from Haining, China. - Chengquan Zhou; Hongbao Ye; Dawei Sun; Jibo Yue; Guijun Yang; Jun Hu (Int. J. Appl. Earth Obs. Geoinformation, 2022)

Multi-feature decision fusion algorithm for disease detection on crop surface based on machine vision. - Shan Hua; Minjie Xu; Zhifu Xu; Hongbao Ye; Chengquan Zhou (Neural Comput. Appl., 2022)

A Robust Deep Learning Approach for the Quantitative Characterization and Clustering of Peach Tree Crowns Based on UAV Images. - Jun Hu; Yanfeng Zhang; Dandan Zhao; Guijun Yang; Feiyun Chen; Chengquan Zhou; Wenxuan Chen (IEEE Trans. Geosci. Remote. Sens., 2022)

Estimating vertically growing crop above-ground biomass based on UAV remote sensing. - Jibo Yue; Hao Yang 009; Guijun Yang; Yuanyuan Fu; Han Wang; Chengquan Zhou (Comput. Electron. Agric., 2023)

Hyperspectral-to-image transform and CNN transfer learning enhancing soybean LCC estimation. - Jibo Yue; Hao Yang 009; Haikuan Feng; Shaoyu Han; Chengquan Zhou; Yuanyuan Fu; Wei Guo 029; Xinming Ma; Hongbo Qiao; Guijun Yang (Comput. Electron. Agric., 2023)

Mapping cropland rice residue cover using a radiative transfer model and deep learning. - Jibo Yue; Qingjiu Tian; Yang Liu 251; Yuanyuan Fu; Jia Tian; Chengquan Zhou; Haikuan Feng; Guijun Yang (Comput. Electron. Agric., 2023)