| 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 | 159 | 2018 |
| In-field high-throughput phenotyping of cotton plant height using LiDAR S Sun, C Li, AH Paterson Remote Sensing 9 (4), 377, 2017 | 129 | 2017 |
| 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 | 112 | 2018 |
| Simulation of an autonomous mobile robot for LiDAR-based in-field phenotyping and navigation J Iqbal, R Xu, S Sun, C Li Robotics 9 (2), 46, 2020 | 109 | 2020 |
| 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 | 108 | 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 | 91 | 2018 |
| Image processing algorithms for infield single cotton boll counting and yield prediction S Sun, C Li, AH Paterson, PW Chee, JS Robertson Computers and electronics in agriculture 166, 104976, 2019 | 58 | 2019 |
| 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 | 56 | 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 | 46 | 2018 |
| High resolution 3D terrestrial LiDAR for cotton plant main stalk and node detection S Sun, C Li, PW Chee, AH Paterson, C Meng, J Zhang, P Ma, ... Computers and electronics in agriculture 187, 106276, 2021 | 36 | 2021 |
| Augmented reality for food quality assessment: Bridging the physical and digital worlds JT Liberty, S Sun, C Kucha, AA Adedeji, G Agidi, MO Ngadi Journal of Food Engineering 367, 111893, 2024 | 16 | 2024 |
| Cotton plant part 3D segmentation and architectural trait extraction using point voxel convolutional neural networks F Saeed, S Sun, J Rodriguez-Sanchez, J Snider, T Liu, C Li Plant methods 19 (1), 33, 2023 | 15 | 2023 |
| Fault diagnosis in railway track circuits using support vector machines S Sun, H Zhao 2013 12th International Conference on Machine Learning and Applications 2 …, 2013 | 15 | 2013 |
| Eff-3dpseg: 3d organ-level plant shoot segmentation using annotation-efficient deep learning L Luo, X Jiang, Y Yang, ERA Samy, M Lefsrud, V Hoyos-Villegas, S Sun Plant Phenomics 5, 0080, 2023 | 11 | 2023 |
| The method of fault detection of compensation capacitor in jointless track circuit based on phase space reconstruction SP Sun, HB Zhao Journal of the China railway society 34 (10), 79-84, 2012 | 10 | 2012 |
| Eff-3DPSeg: 3D organ-level plant shoot segmentation using annotation-efficient point clouds L Luo, X Jiang, Y Yang, ERA Samy, M Lefsrud, V Hoyos-Villegas, S Sun arXiv preprint arXiv:2212.10263, 2022 | 9 | 2022 |
| Rapid determination of the roasting degree of cocoa beans by extreme learning machine (ELM)-based imaging analysis Y Yang, AG Darwish, I El-Sharkawy, Q Zhu, S Sun, J Tan Journal of Agriculture and Food Research 10, 100437, 2022 | 9 | 2022 |
| 3D computer vision and machine learning based technique for high throughput cotton boll mapping under field conditions S Sun, C Li, A Paterson, Y Jiang, J Robertson 2018 ASABE Annual International Meeting, 1, 2018 | 9 | 2018 |
| PEAMATL: A strategy for developing near-infrared spectral prediction models under domain shift using self-supervised transfer learning Y Yang, S Sun, M Huang, Q Zhu IEEE Transactions on Instrumentation and Measurement 72, 1-12, 2023 | 8 | 2023 |
| Predictions of multiple food quality parameters using near-infrared spectroscopy with a novel multi-task genetic programming approach Y Yang, S Sun, L Pan, M Huang, Q Zhu Food Control 144, 109389, 2023 | 8 | 2023 |
Changying LiProfessor of Agricultural & Biological Engineering, University of Florida; Adjunct Professor at UGAE-mail megerősítve itt: ufl.edu