| Application of deep learning in food: a review L Zhou, C Zhang, F Liu, Z Qiu, Y He Comprehensive reviews in food science and food safety 18 (6), 1793-1811, 2019 | 507 | 2019 |
| Developing deep learning based regression approaches for determination of chemical compositions in dry black goji berries (Lycium ruthenicum Murr.) using near-infrared … C Zhang, W Wu, L Zhou, H Cheng, X Ye, Y He Food chemistry 319, 126536, 2020 | 180 | 2020 |
| Detection of adulteration in food based on nondestructive analysis techniques: A review Y He, X Bai, Q Xiao, F Liu, L Zhou, C Zhang Critical Reviews in Food Science and Nutrition 61 (14), 2351-2371, 2021 | 119 | 2021 |
| Near-infrared hyperspectral imaging combined with deep learning to identify cotton seed varieties S Zhu, L Zhou, P Gao, Y Bao, Y He, L Feng Molecules 24 (18), 3268, 2019 | 106 | 2019 |
| Information fusion of emerging non-destructive analytical techniques for food quality authentication: A survey L Zhou, C Zhang, Z Qiu, Y He TrAC Trends in Analytical Chemistry 127, 115901, 2020 | 92 | 2020 |
| Recent progress of nondestructive techniques for fruits damage inspection: a review Y He, Q Xiao, X Bai, L Zhou, F Liu, C Zhang Critical Reviews in Food Science and Nutrition 62 (20), 5476-5494, 2022 | 73 | 2022 |
| Recent advances of smart systems and internet of things (iot) for aquaponics automation: A comprehensive overview MF Taha, G ElMasry, M Gouda, L Zhou, N Liang, A Abdalla, D Rousseau, ... Chemosensors 10 (8), 303, 2022 | 68 | 2022 |
| Wheat kernel variety identification based on a large near-infrared spectral dataset and a novel deep learning-based feature selection method L Zhou, C Zhang, MF Taha, X Wei, Y He, Z Qiu, Y Liu Frontiers in plant science 11, 575810, 2020 | 67 | 2020 |
| Noise reduction in the spectral domain of hyperspectral images using denoising autoencoder methods C Zhang, L Zhou, Y Zhao, S Zhu, F Liu, Y He Chemometrics and Intelligent Laboratory Systems 203, 104063, 2020 | 67 | 2020 |
| GainTKW: a measurement system of thousand kernel weight based on the android platform W Wu, L Zhou, J Chen, Z Qiu, Y He Agronomy 8 (9), 178, 2018 | 67 | 2018 |
| Detection of subtle bruises on winter jujube using hyperspectral imaging with pixel-wise deep learning method L Feng, S Zhu, L Zhou, Y Zhao, Y Bao, C Zhang, Y He IEEE access 7, 64494-64505, 2019 | 59 | 2019 |
| Identification of soybean varieties using hyperspectral imaging coupled with convolutional neural network S Zhu, L Zhou, C Zhang, Y Bao, B Wu, H Chu, Y Yu, Y He, L Feng Sensors 19 (19), 4065, 2019 | 52 | 2019 |
| Fusion of feature selection methods and regression algorithms for predicting the canopy water content of rice based on hyperspectral data O Elsherbiny, Y Fan, L Zhou, Z Qiu Agriculture 11 (1), 51, 2021 | 50 | 2021 |
| Using deep convolutional neural network for image-based diagnosis of nutrient deficiencies in plants grown in aquaponics MF Taha, A Abdalla, G ElMasry, M Gouda, L Zhou, N Zhao, N Liang, Z Niu, ... Chemosensors 10 (2), 45, 2022 | 49 | 2022 |
| Vision-based moving obstacle detection and tracking in paddy field using improved yolov3 and deep SORT Z Qiu, N Zhao, L Zhou, M Wang, L Yang, H Fang, Y He, Y Liu Sensors 20 (15), 4082, 2020 | 48 | 2020 |
| Spectral preprocessing combined with deep transfer learning to evaluate chlorophyll content in cotton leaves Q Xiao, W Tang, C Zhang, L Zhou, L Feng, J Shen, T Yan, P Gao, Y He, ... Plant Phenomics, 2022 | 38 | 2022 |
| Integration of visible and thermal imagery with an artificial neural network approach for robust forecasting of canopy water content in rice O Elsherbiny, L Zhou, L Feng, Z Qiu Remote Sensing 13 (9), 1785, 2021 | 35 | 2021 |
| A portable NIR-system for mixture powdery food analysis using deep learning L Zhou, L Tan, C Zhang, N Zhao, Y He, Z Qiu Lwt 153, 112456, 2022 | 32 | 2022 |
| End-to-end fusion of hyperspectral and chlorophyll fluorescence imaging to identify rice stresses C Zhang, L Zhou, Q Xiao, X Bai, B Wu, N Wu, Y Zhao, J Wang, L Feng Plant Phenomics, 2022 | 30 | 2022 |
| Development of an automatic pest monitoring system using a deep learning model of DPeNet N Zhao, L Zhou, T Huang, MF Taha, Y He, Z Qiu Measurement 203, 111970, 2022 | 26 | 2022 |
