Grain yield prediction of rice using multi-temporal UAV-based RGB and multispectral images and model transfer–a case study of small farmlands in the South of China L Wan, H Cen, J Zhu, J Zhang, Y Zhu, D Sun, X Du, L Zhai, H Weng, Y Li, ... Agricultural and Forest Meteorology 291, 108096, 2020 | 229 | 2020 |
Combining UAV-based vegetation indices and image classification to estimate flower number in oilseed rape L Wan, Y Li, H Cen, J Zhu, W Yin, W Wu, H Zhu, D Sun, W Zhou, Y He Remote Sensing 10 (9), 1484, 2018 | 151 | 2018 |
Dynamic monitoring of biomass of rice under different nitrogen treatments using a lightweight UAV with dual image-frame snapshot cameras H Cen, L Wan, J Zhu, Y Li, X Li, Y Zhu, H Weng, W Wu, W Yin, C Xu, ... Plant Methods 15, 1-16, 2019 | 145 | 2019 |
Fine-tuning convolutional neural network with transfer learning for semantic segmentation of ground-level oilseed rape images in a field with high weed pressure A Abdalla, H Cen, L Wan, R Rashid, H Weng, W Zhou, Y He Computers and electronics in agriculture 167, 105091, 2019 | 140 | 2019 |
Using hyperspectral analysis as a potential high throughput phenotyping tool in GWAS for protein content of rice quality D Sun, H Cen, H Weng, L Wan, A Abdalla, AI El-Manawy, Y Zhu, N Zhao, ... Plant methods 15, 1-16, 2019 | 76 | 2019 |
Combining transfer learning and hyperspectral reflectance analysis to assess leaf nitrogen concentration across different plant species datasets L Wan, W Zhou, Y He, TC Wanger, H Cen Remote Sensing of Environment 269, 112826, 2022 | 62 | 2022 |
Nutrient status diagnosis of infield oilseed rape via deep learning-enabled dynamic model A Abdalla, H Cen, L Wan, K Mehmood, Y He IEEE Transactions on Industrial Informatics 17 (6), 4379-4389, 2020 | 62 | 2020 |
Unmanned aerial vehicle-based field phenotyping of crop biomass using growth traits retrieved from PROSAIL model L Wan, J Zhang, X Dong, X Du, J Zhu, D Sun, Y Liu, Y He, H Cen Computers and Electronics in Agriculture 187, 106304, 2021 | 51 | 2021 |
Current status and future perspective of the application of deep learning in plant phenotype research H Cen, Y Zhu, D Sun, L Zhai, L Wan, ZH Ma, Z Liu, Y He Trans. Chin. Soc. Agric. Eng 36 (9), 1-16, 2020 | 50* | 2020 |
A model for phenotyping crop fractional vegetation cover using imagery from unmanned aerial vehicles L Wan, J Zhu, X Du, J Zhang, X Han, W Zhou, X Li, J Liu, F Liang, Y He, ... Journal of experimental botany 72 (13), 4691-4707, 2021 | 42 | 2021 |
Color calibration of proximal sensing RGB images of oilseed rape canopy via deep learning combined with K-means algorithm A Abdalla, H Cen, E Abdel-Rahman, L Wan, Y He Remote Sensing 11 (24), 3001, 2019 | 37 | 2019 |
Spatiotemporal Heterogeneity of Chlorophyll Content and Fluorescence Response Within Rice (Oryza sativa L.) Canopies Under Different Nitrogen Treatments J Zhang, L Wan, C Igathinathane, Z Zhang, Y Guo, D Sun, H Cen Frontiers in plant science 12, 645977, 2021 | 33 | 2021 |
PROSDM: Applicability of PROSPECT model coupled with spectral derivatives and similarity metrics to retrieve leaf biochemical traits from bidirectional reflectance L Wan, J Zhang, Y Xu, Y Huang, W Zhou, L Jiang, Y He, H Cen Remote Sensing of Environment 267, 112761, 2021 | 30 | 2021 |
Multi-temporal monitoring of leaf area index of rice under different nitrogen treatments using UAV images X Du, L Wan, H Cen, S Chen, J Zhu, H Wang, Y He International Journal of Precision Agricultural Aviation 3 (1), 2020 | 19 | 2020 |
Upscaling from leaf to canopy: Improved spectral indices for leaf biochemical traits estimation by minimizing the difference between leaf adaxial and abaxial surfaces L Wan, Z Tang, J Zhang, S Chen, W Zhou, H Cen Field Crops Research 274, 108330, 2021 | 18 | 2021 |
Using fusion of texture features and vegetation indices from water concentration in rice crop to UAV remote sensing monitor W Liang, C Haiyan, Z Jiangpeng, Z Jiafei, D Xiaoyue, H Yong Smart Agriculture 2 (1), 58, 2020 | 17* | 2020 |
UAV time-series imagery with novel machine learning to estimate heading dates of rice accessions for breeding M Lyu, X Lu, Y Shen, Y Tan, L Wan, Q Shu, Y He, Y He, H Cen Agricultural and Forest Meteorology 341, 109646, 2023 | 15 | 2023 |
Characterization and detection of leaf photosynthetic response to citrus Huanglongbing from cool to hot seasons in two orchards H Weng, Y Zeng, H Cen, M He, Y Meng, Y Liu, L Wan, H Xu, H Li, H Fang, ... Transactions of the ASABE 63 (2), 501-512, 2020 | 12 | 2020 |
Rapid detection of citrus Huanglongbing based on chlorophyll fluorescence imaging technology H Weng, C He, J Xu, L Liu, J Qing, L Wan, D Ye Trans. CSAE 36, 196-203, 2020 | 11* | 2020 |
Improving retrieval of leaf chlorophyll content from Sentinel-2 and Landsat-7/8 imagery by correcting for canopy structural effects L Wan, Y Ryu, B Dechant, J Lee, Z Zhong, H Feng Remote Sensing of Environment 304, 114048, 2024 | 10 | 2024 |