| CNN feature based graph convolutional network for weed and crop recognition in smart farming H Jiang, C Zhang, Y Qiao, Z Zhang, W Zhang, C Song Computers and electronics in agriculture 174, 105450, 2020 | 198 | 2020 |
| Cattle segmentation and contour extraction based on Mask R-CNN for precision livestock farming Y Qiao, M Truman, S Sukkarieh Computers and Electronics in Agriculture 165, 104958, 2019 | 186 | 2019 |
| Intelligent perception for cattle monitoring: A review for cattle identification, body condition score evaluation, and weight estimation Y Qiao, H Kong, C Clark, S Lomax, D Su, S Eiffert, S Sukkarieh Computers and electronics in agriculture 185, 106143, 2021 | 128 | 2021 |
| Data augmentation for deep learning based semantic segmentation and crop-weed classification in agricultural robotics D Su, H Kong, Y Qiao, S Sukkarieh Computers and Electronics in Agriculture 190, 106418, 2021 | 93 | 2021 |
| Individual cattle identification using a deep learning based framework Y Qiao, D Su, H Kong, S Sukkarieh, S Lomax, C Clark IFAC-PapersOnLine 52 (30), 318-323, 2019 | 88 | 2019 |
| An improved YOLOv5-based vegetable disease detection method J Li, Y Qiao, S Liu, J Zhang, Z Yang, M Wang Computers and Electronics in Agriculture 202, 107345, 2022 | 76 | 2022 |
| Real time detection of inter-row ryegrass in wheat farms using deep learning D Su, Y Qiao, H Kong, S Sukkarieh Biosystems Engineering 204, 198-211, 2021 | 54 | 2021 |
| C3D-ConvLSTM based cow behaviour classification using video data for precision livestock farming Y Qiao, Y Guo, K Yu, D He Computers and electronics in agriculture 193, 106650, 2022 | 48 | 2022 |
| Cattle body detection based on YOLOv5-ASFF for precision livestock farming Y Qiao, Y Guo, D He Computers and Electronics in Agriculture 204, 107579, 2023 | 47 | 2023 |
| The research progress of vision-based artificial intelligence in smart pig farming S Wang, H Jiang, Y Qiao, S Jiang, H Lin, Q Sun Sensors 22 (17), 6541, 2022 | 46 | 2022 |
| Weed recognition based on SVM-DS multi-feature fusion. HDJ He DongJian, QYL Qiao YongLiang, LP Li Pan, GZ Gao Zhan, ... | 40 | 2013 |
| BiLSTM-based individual cattle identification for automated precision livestock farming Y Qiao, D Su, H Kong, S Sukkarieh, S Lomax, C Clark 2020 IEEE 16th International Conference on Automation Science and …, 2020 | 38 | 2020 |
| Intelligent perception-based cattle lameness detection and behaviour recognition: A review Y Qiao, H Kong, C Clark, S Lomax, D Su, S Eiffert, S Sukkarieh Animals 11 (11), 3033, 2021 | 37 | 2021 |
| Identification method of multi-feature weed based on multi-spectral images and data mining C Zhao, D He, Y Qiao Transactions of the Chinese Society of Agricultural Engineering 29 (2), 192-198, 2013 | 29 | 2013 |
| Deep learning based automatic grape downy mildew detection Z Zhang, Y Qiao, Y Guo, D He Frontiers in Plant Science 13, 872107, 2022 | 28 | 2022 |
| Multiframe-based high dynamic range monocular vision system for advanced driver assistance systems Y Li, Y Qiao, Y Ruichek IEEE Sensors Journal 15 (10), 5433-5441, 2015 | 25 | 2015 |
| Data augmentation for deep learning based cattle segmentation in precision livestock farming Y Qiao, D Su, H Kong, S Sukkarieh, S Lomax, C Clark 2020 IEEE 16th International Conference on Automation Science and …, 2020 | 24 | 2020 |
| Automated aerial animal detection when spatial resolution conditions are varied J Brown, Y Qiao, C Clark, S Lomax, K Rafique, S Sukkarieh Computers and Electronics in Agriculture 193, 106689, 2022 | 23 | 2022 |
| ConvNet and LSH-based visual localization using localized sequence matching Y Qiao, C Cappelle, Y Ruichek, T Yang Sensors 19 (11), 2439, 2019 | 23 | 2019 |
| Filtering for systems subject to unknown inputs without a priori initial information H Kong, M Shan, D Su, Y Qiao, A Al-Azzawi, S Sukkarieh Automatica 120, 109122, 2020 | 22 | 2020 |
Daobilige SuChina Agricultural UniversityVerified email at cau.edu.cn
