| Do we really need deep CNN for plant diseases identification? Y Li, J Nie, X Chao Computers and Electronics in Agriculture 178, 105803, 2020 | 212 | 2020 |
| Few-shot cotton pest recognition and terminal realization Y Li, J Yang Computers and Electronics in Agriculture 169, 105240, 2020 | 163 | 2020 |
| Meta-learning baselines and database for few-shot classification in agriculture Y Li, J Yang Computers and Electronics in Agriculture 182, 106055, 2021 | 135 | 2021 |
| Semi-supervised few-shot learning approach for plant diseases recognition Y Li, X Chao Plant Methods 17, 1-10, 2021 | 123 | 2021 |
| A survey of few-shot learning in smart agriculture: developments, applications, and challenges J Yang, X Guo, Y Li, F Marinello, S Ercisli, Z Zhang Plant Methods 18 (1), 28, 2022 | 116 | 2022 |
| Msta-net: forgery detection by generating manipulation trace based on multi-scale self-texture attention J Yang, S Xiao, A Li, W Lu, X Gao, Y Li IEEE Transactions on Circuits and Systems for Video Technology 32 (7), 4854-4866, 2021 | 97 | 2021 |
| ANN-based continual classification in agriculture Y Li, X Chao Agriculture Basel 10 (5), 178, 2020 | 84 | 2020 |
| Comprehensive ocean information-enabled AUV path planning via reinforcement learning M Xi, J Yang, J Wen, H Liu, Y Li, HH Song IEEE Internet of Things Journal 9 (18), 17440-17451, 2022 | 75 | 2022 |
| Artificial intelligence and digital twins in sustainable agriculture and forestry: A survey J Nie, Y Wang, Y Li, X Chao Turkish Journal of Agriculture and Forestry, 2022 | 73 | 2022 |
| Entropy-based redundancy analysis and information screening Y Li, J Yang, J Wen Digital Communications and Networks, 2023 | 63 | 2023 |
| Distance-entropy: an effective indicator for selecting informative data Y Li, X Chao Frontiers in Plant Science, 2022 | 63 | 2022 |
| Healthcare Data Quality Assessment for Cybersecurity Intelligence Y Li, J Yang, Z Zhang, J Wen, P Kumar IEEE Transactions on Industrial Informatics, 2023 | 62 | 2023 |
| Toward sustainability: trade-off between data quality and quantity in crop pest recognition Y Li, X Chao Frontiers in Plant Science 12, 2959, 2021 | 56 | 2021 |
| Sustainable computing in smart agriculture: survey and challenges J Nie, Y Wang, Y Li, X Chao Turkish Journal of Agriculture and Forestry 46 (4), 550-566, 2022 | 54 | 2022 |
| Dissimilarity-based active learning for embedded weed identification Y Yang, Y Li, J Yang, J Wen Turkish Journal of Agriculture and Forestry 46 (3), 390-401, 2022 | 52 | 2022 |
| Data quality assessment and analysis for pest identification in smart agriculture J Yang, G Lan, Y Li, Y Gong, Z Zhang, S Ercisli Computers and Electrical Engineering 103, 108322, 2022 | 48 | 2022 |
| Disturbed-entropy: A simple data quality assessment approach Y Li, X Chao, S Ercisli ICT Express 8 (3), 309-312, 2022 | 45 | 2022 |
| Behavior-Based Formation Control Digital Twin for Multi-AUG in Edge Computing J Wen, J Yang, Y Li, J He, Z Li, H Song IEEE Transactions on Network Science and Engineering, 2022 | 43 | 2022 |
| Intelligent Path Planning of Underwater Robot Based on Reinforcement Learning J Yang, J Ni, M Xi, J Wen, Y Li IEEE Transactions on Automation Science and Engineering, 2022 | 42 | 2022 |
| The intelligent path planning system of agricultural robot via reinforcement learning J Yang, J Ni, Y Li, J Wen, D Chen Sensors 22 (12), 4316, 2022 | 41 | 2022 |
