Chengquan Zhou
Orcid: 0000-0001-7427-0888
According to our database1,
Chengquan Zhou
authored at least 17 papers
between 2018 and 2023.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2023
Mapping cropland rice residue cover using a radiative transfer model and deep learning.
Comput. Electron. Agric., December, 2023
Hyperspectral-to-image transform and CNN transfer learning enhancing soybean LCC estimation.
Comput. Electron. Agric., August, 2023
Comput. Electron. Agric., February, 2023
2022
A Robust Deep Learning Approach for the Quantitative Characterization and Clustering of Peach Tree Crowns Based on UAV Images.
IEEE Trans. Geosci. Remote. Sens., 2022
Multi-feature decision fusion algorithm for disease detection on crop surface based on machine vision.
Neural Comput. Appl., 2022
An automated, high-performance approach for detecting and characterizing broccoli based on UAV remote-sensing and transformers: A case study from Haining, China.
Int. J. Appl. Earth Obs. Geoinformation, 2022
2021
Real-time nondestructive fish behavior detecting in mixed polyculture system using deep-learning and low-cost devices.
Expert Syst. Appl., 2021
Recognizing black point in wheat kernels and determining its extent using multidimensional feature extraction and a naive Bayes classifier.
Comput. Electron. Agric., 2021
2019
Automated Counting of Rice Panicle by Applying Deep Learning Model to Images from Unmanned Aerial Vehicle Platform.
Sensors, 2019
Using Hyperspectral Crop Residue Angle Index to Estimate Maize and Winter-Wheat Residue Cover: A Laboratory Study.
Remote. Sens., 2019
A dynamic soil endmember spectrum selection approach for soil and crop residue linear spectral unmixing analysis.
Int. J. Appl. Earth Obs. Geoinformation, 2019
Combined Use of FCN and Harris Corner Detection for Counting Wheat Ears in Field Conditions.
IEEE Access, 2019
2018
An Integrated Skeleton Extraction and Pruning Method for Spatial Recognition of Maize Seedlings in MGV and UAV Remote Images.
IEEE Trans. Geosci. Remote. Sens., 2018
Fusion of Unmanned Aerial Vehicle Panchromatic and Hyperspectral Images Combining Joint Skewness-Kurtosis Figures and a Non-Subsampled Contourlet Transform.
Sensors, 2018
Recognition of Wheat Spike from Field Based Phenotype Platform Using Multi-Sensor Fusion and Improved Maximum Entropy Segmentation Algorithms.
Remote. Sens., 2018
A Comparison of Crop Parameters Estimation Using Images from UAV-Mounted Snapshot Hyperspectral Sensor and High-Definition Digital Camera.
Remote. Sens., 2018
Quantitative Identification of Maize Lodging-Causing Feature Factors Using Unmanned Aerial Vehicle Images and a Nomogram Computation.
Remote. Sens., 2018