| Weed identification using deep learning and image processing in vegetable plantation X Jin, J Che, Y Chen IEEE Access 9, 10940-10950, 2021 | 211 | 2021 |
| A novel deep learning‐based method for detection of weeds in vegetables X Jin, Y Sun, J Che, M Bagavathiannan, J Yu, Y Chen Pest Management Science 78 (5), 1861-1869, 2022 | 106 | 2022 |
| Evaluation of different deep convolutional neural networks for detection of broadleaf weed seedlings in wheat J Zhuang, X Li, M Bagavathiannan, X Jin, J Yang, W Meng, T Li, L Li, ... Pest Management Science 78 (2), 521–529, 2021 | 46 | 2021 |
| Deep learning for detecting herbicide weed control spectrum in turfgrass X Jin, M Bagavathiannan, A Maity, Y Chen, J Yu Plant Methods 18, 94, 2022 | 38 | 2022 |
| A deep learning‐based method for classification, detection, and localization of weeds in turfgrass X Jin, M Bagavathiannan, PE McCullough, Y Chen, J Yu Pest Management Science 78 (11), 4809-4821, 2022 | 28 | 2022 |
| Deep learning-based weed detection in turf: a review X Jin, T Liu, Y Chen, J Yu Agronomy 12 (12), 3051, 2022 | 27 | 2022 |
| Research on a parallel robot for tea flushes plucking J Chen, Y Chen, X Jin, J Che, F Gao, N Li 2015 International Conference on Education, Management, Information and …, 2015 | 20 | 2015 |
| Semi-supervised learning and attention mechanism for weed detection in wheat T Liu, X Jin, L Zhang, J Wang, Y Chen, C Hu, J Yu Crop Protection 174, 106389, 2023 | 17 | 2023 |
| Precision weed control using a smart sprayer in dormant bermudagrass turf X Jin, T Liu, Z Yang, J Xie, M Bagavathiannan, X Hong, Z Xu, X Chen, ... Crop Protection 172, 106302, 2023 | 17 | 2023 |
| 自然环境下茶树嫩梢识别方法研究 韦佳佳， 陈勇， 金小俊， 郑加强， 石元值， 张浩 茶叶科学 32 (5), 377-381, 2019 | 16 | 2019 |
| A smart sprayer for weed control in bermudagrass turf based on the herbicide weed control spectrum X Jin, PE McCullough, T Liu, D Yang, W Zhu, Y Chen, J Yu Crop Protection 170, 106270, 2023 | 14 | 2023 |
| Intra-row weed recognition using plant spacing information in stereo images Y Chen, X Jin, L Tang, J Che, Y Sun, J Chen 2013 Kansas City, Missouri, July 21-July 24, 2013, 1, 2013 | 13 | 2013 |
| Researches on tender tea shoots identification under natural conditions. J Wei, Y Chen, X Jin, J Zheng, Y Shi, H Zhang | 12 | 2012 |
| Evaluation of convolutional neural networks for herbicide susceptibility-based weed detection in turf X Jin, T Liu, PE McCullough, Y Chen, J Yu Frontiers in Plant Science 14, 1096802, 2023 | 10 | 2023 |
| Drought stress impact on the performance of deep convolutional neural networks for weed detection in Bahiagrass J Zhuang, X Jin, Y Chen, W Meng, Y Wang, J Yu, B Muthukumar Grass and Forage Science 78 (1), 214-223, 2022 | 10 | 2022 |
| High-quality tea flushes detection under natural conditions using computer vision X Jin, Y Chen, H Zhang, Y Sun, J Chen International Journal of Digital Content Technology and its Applications 6 …, 2012 | 10 | 2012 |
| TSP-yolo-based deep learning method for monitoring cabbage seedling emergence X Chen, T Liu, K Han, X Jin, J Wang, X Kong, J Yu European Journal of Agronomy 157, 127191, 2024 | 9 | 2024 |
| Detection and coverage estimation of purple nutsedge in turf with image classification neural networks X Jin, K Han, H Zhao, Y Wang, Y Chen, J Yu Pest Management Science 80 (7), 3504-3515, 2024 | 8 | 2024 |
| 基于 Bayes 与 SVM 的玉米彩色图像分割新算法 程玉柱， 陈勇， 车军， 金小俊 江苏农业科学 40 (7), 355-358, 2012 | 8 | 2012 |
| AI differentiation of bok choy seedlings from weeds Y Sun, Y Chen, X Jin, J Yu, Y Chen Fujian Journal of Agricultural Sciences 36 (12), 1484-1490, 2021 | 7 | 2021 |
Muthukumar BagavathiannanTexas A&M University, College Station, TX, USAE-mailová adresa ověřena na: tamu.edu