Convolutional neural networks for image-based high-throughput plant phenotyping: a review Y Jiang, C Li Plant Phenomics, 2020 | 233 | 2020 |
In-field high throughput phenotyping and cotton plant growth analysis using LiDAR S Sun, C Li, AH Paterson, Y Jiang, R Xu, JS Robertson, JL Snider, ... Frontiers in plant science 9, 16, 2018 | 140 | 2018 |
High throughput phenotyping of cotton plant height using depth images under field conditions Y Jiang, C Li, AH Paterson Computers and Electronics in Agriculture 130, 57-68, 2016 | 127 | 2016 |
Prediction of dissolved oxygen content in river crab culture based on least squares support vector regression optimized by improved particle swarm optimization S Liu, L Xu, D Li, Q Li, Y Jiang, H Tai, L Zeng Computers and Electronics in Agriculture 95, 82-91, 2013 | 108 | 2013 |
Aerial images and convolutional neural network for cotton bloom detection R Xu, C Li, AH Paterson, Y Jiang, S Sun, JS Robertson Frontiers in plant science 8, 2235, 2018 | 101 | 2018 |
A hybrid WA–CPSO-LSSVR model for dissolved oxygen content prediction in crab culture S Liu, L Xu, Y Jiang, D Li, Y Chen, Z Li Engineering Applications of Artificial Intelligence 29, 114-124, 2014 | 93 | 2014 |
DeepSeedling: Deep convolutional network and Kalman filter for plant seedling detection and counting in the field Y Jiang, C Li, AH Paterson, JS Robertson Plant methods 15 (1), 141, 2019 | 92 | 2019 |
Three-dimensional photogrammetric mapping of cotton bolls in situ based on point cloud segmentation and clustering S Sun, C Li, PW Chee, AH Paterson, Y Jiang, R Xu, JS Robertson, ... ISPRS Journal of Photogrammetry and Remote Sensing 160, 195-207, 2020 | 90 | 2020 |
GPhenoVision: A ground mobile system with multi-modal imaging for field-based high throughput phenotyping of cotton Y Jiang, C Li, JS Robertson, S Sun, R Xu, AH Paterson Scientific reports 8 (1), 1213, 2018 | 78 | 2018 |
Fully convolutional networks for blueberry bruising and calyx segmentation using hyperspectral transmittance imaging M Zhang, Y Jiang, C Li, F Yang Biosystems Engineering 192, 159-175, 2020 | 66 | 2020 |
Nondestructive detection and quantification of blueberry bruising using near-infrared (NIR) hyperspectral reflectance imaging Y Jiang, C Li, F Takeda Scientific Reports 6 (1), 35679, 2016 | 63 | 2016 |
Blueberry bruise detection by pulsed thermographic imaging J Kuzy, Y Jiang, C Li Postharvest Biology and Technology 136, 166-177, 2018 | 62 | 2018 |
mRMR-based feature selection for classification of cotton foreign matter using hyperspectral imaging Y Jiang, C Li Computers and electronics in agriculture 119, 191-200, 2015 | 47 | 2015 |
DeepFlower: a deep learning-based approach to characterize flowering patterns of cotton plants in the field Y Jiang, C Li, R Xu, S Sun, JS Robertson, AH Paterson Plant methods 16, 1-17, 2020 | 44 | 2020 |
Quantitative analysis of cotton canopy size in field conditions using a consumer-grade RGB-D camera Y Jiang, C Li, AH Paterson, S Sun, R Xu, J Robertson Frontiers in plant science 8, 2233, 2018 | 44 | 2018 |
3D point cloud data to quantitatively characterize size and shape of shrub crops Y Jiang, C Li, F Takeda, EA Kramer, H Ashrafi, J Hunter Horticulture research 6, 2019 | 40 | 2019 |
Detection and discrimination of cotton foreign matter using push-broom based hyperspectral imaging: System design and capability Y Jiang, C Li PLoS One 10 (3), e0121969, 2015 | 32 | 2015 |
Morphometric relationships and their contribution to biomass and cannabinoid yield in hybrids of hemp (Cannabis sativa) CH Carlson, GM Stack, Y Jiang, B Taşkıran, AR Cala, JA Toth, G Philippe, ... Journal of Experimental Botany 72 (22), 7694-7709, 2021 | 28 | 2021 |
An improved gray model for aquaculture water quality prediction Z Li, Y Jiang, J Yue, L Zhang, D Li Intelligent Automation & Soft Computing 18 (5), 557-567, 2012 | 25 | 2012 |
Cotton contamination detection and classification using hyperspectral fluorescence imaging A Mustafic, Y Jiang, C Li Textile research journal 86 (15), 1574-1584, 2016 | 20 | 2016 |