Lightweight modified attention based deep learning model for cassava leaf diseases classification-Reference-Cited by-同舟云学术

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Lightweight modified attention based deep learning model for cassava leaf diseases classification

Published:2023-12-19 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Tewari Anand Shanker^ORCID,Kumari Priya

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

Cited by 2 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

1. Comparative Analysis of Cassava Leaf Disease Prediction Using the Deep Learning Approach;2024 2nd International Conference on Sustainable Computing and Smart Systems (ICSCSS);2024-07-10

2. CNN Design with AlexNet Algorithm for Diagnosis of Diseases in Cassava Leaves;2024 International Conference on Expert Clouds and Applications (ICOECA);2024-04-18

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