Author:
Augustin Anju,Kiliroor Cinu C.
Publisher
Springer Nature Switzerland
Reference12 articles.
1. Devi, D., Anand, A., Sophia, S., Karpagam, M.: IoT deep learning based prediction of amount of pesticides and diseases in fruits. In: Conference Proceeding of the International Conference on Smart Electronics and Communication (ICOSEC 2020), pp. 848–853. IEEE Xplore (2020)
2. Sellamuthu, K., Kaliappan, V.K.: Q-learning based pesticide contamination prediction in vegetables and fruits. Comput. Sci. Eng. 45(1), 715–736 (2023)
3. Jiang, B., He, J., Yang, S., Fu, H.: Fusion of machine vision technology and AlexNet- CNN deep learning networks for detection of post-harvest apple pesticide. Artif. Intell. Agric. 1, 1–8 (2019)
4. Ahmad, A., Gamal, A.E., Saraswat, D.: Towards generalization of deep learning based plant disease identification under controlled and field condition. IEEE Access 11, 9042–9057 (2023)
5. Ye, W., Yan, T., Zhang, C., Duan, L.: Detection of pesticide residue level in grape using hyperspectral imaging with machine learning. Foods 11(11), 1609 (2022)
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献