A Comprehensive Review on Crop Disease Prediction Based on Machine Learning and Deep Learning Techniques
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-9225-4_36
Reference75 articles.
1. Shrivastava VK, Pradhan MK (2021) Rice plant disease classification using color features: a machine learning paradigm. J Plant Pathol 103(1):17–26
2. Jothiaruna N, Joseph Abraham Sundar K, Ifjaz Ahmed M (2021) A disease spot segmentation method using comprehensive color feature with multi-resolution channel and region growing. Multimed Tools Appl 80(3):3327–3335
3. Fuentes A, Yoon S, Kim SC, Park DS (2017) A robust deep-learning-based detector for real-time tomato plant diseases and pests recognition. Sensors 17(9):2022
4. Fuentes AF, Yoon S, Lee J, Park DS (2018) High-performance deep neural network-based tomato plant diseases and pests diagnosis system with refinement filter bank. Front Plant Sci 9:1162
5. Pham TN, Tran LV, Dao SVT (2020) Early disease classification of mango leaves using feed-forward neural network and hybrid metaheuristic feature selection. IEEE Access 8:189960–189973
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