Lightweight modified attention based deep learning model for cassava leaf diseases classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17459-3.pdf
Reference52 articles.
1. Sambasivam G, Opiyo GD (2021) A predictive machine learning application in agriculture: Cassava disease detection and classification with imbal- anced dataset using convolutional neural networks. Egypt Inform J 22(1):27–34
2. Methil A, Agrawal H, Kaushik V (2021) One-vs-all methodology based cas- sava leaf disease detection. In: 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT), pp. 1–7. IEEE
3. Singh V, Misra AK (2017) Detection of plant leaf diseases using image segmentation and soft computing techniques. Inf Process Agric. 4(1):41–49
4. Taiwo KA (2006) Utilization potentials of cassava in nigeria: the domestic and industrial products. Food Rev Int 22(1):29–42
5. Thresh J, Cooter R (2005) Strategies for controlling cassava mosaic virus disease in africa. Plant pathology 54(5):587–614
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