An Optimized Deep Learning Technique for Enhance Disease Identification in Tomato Leaf to Promote Sustainable Agriculture-Reference-Cited by-同舟云学术

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An Optimized Deep Learning Technique for Enhance Disease Identification in Tomato Leaf to Promote Sustainable Agriculture

Published:2023-10-20 Issue: Volume:11 Page:1-5
ISSN:
Container-title:2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT)
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Author:

Soujanya Thota¹,Padmaja S.²,Ramesh Dadi³,Shabana ⁴,Mohmmad Sallauddin⁵

Affiliation:

1. University Warangal,School of Agriculture SR,India

2. College for Women,Social Welfare Residential Degree,Dept of Computer Science Telangana,Sircilla,India

3. SR University Warangal,School of Computer Science and Artificial Intelligence,India

4. Sumathi Reddy Institute of Technology for Women,Warangal,India

5. SR University,School of Computer Science and Artificaial Intelligence,Warangal,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10391855/10391862/10392310.pdf?arnumber=10392310

Reference22 articles.

1. Farm monitoring and disease prediction by classification based on deep learning architectures in sustainable agriculture

2. A novel framework for image-based plant disease detection using hybrid deep learning approach

3. Plant leaf disease detection using computer vision and machine learning algorithms

4. Seasonal Crops Disease Prediction and Classification Using Deep Convolutional Encoder Network

5. An Application of Machine Learning Technique in Forecasting Crop Disease

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

1. Performance Assessment of Various Deep Learning Based Models for Multiclass Classification of Tomato Leaf Diseases;2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE);2024-05-09

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