Fighting Grape Black Rot with Deep Learning: A CNN-LSTM Hybrid Model for Disease Severity Classification

Author:

Gaur Poonam1,Sharma Rohit2,Kumar Ravi3,Gupta Amit3,Sharma Rishabh4,Kukreja Vinay4

Affiliation:

1. CGC Landran,Department of Computer Application,Mohali

2. College of Engineering, CGC,Chandigarh Group of Technology,Landran

3. Manav Rachna International Institute of Research and Studies

4. Chitkara University Institute of Engineering and Technology, Chitkara University,Punjab,India

Publisher

IEEE

Cited by 10 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. Effective and efficient automatic detection, prediction and prescription of potential disease in berry family;Multimedia Tools and Applications;2024-09-02

2. Black rot disease classification of apples and grapes using convolutional neural network and transfer learning;2024 8th International Conference on Image and Signal Processing and their Applications (ISPA);2024-04-21

3. Deep Learning Meets Support Vector Machines: An Effective Hybrid Model for Banana Leaf Wilt Disease Severity Assessment;2024 2nd International Conference on Disruptive Technologies (ICDT);2024-03-15

4. Rice Sheath Rot Disease Detection and Severity Classification: A Novel Framework Leveraging CNN-LSTM Models for Multi-Classification;2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI);2024-03-14

5. Mitigating Mustard Downy Mildew Disease: Early Detection and Prevention through a Hybrid CNN-SVM Model;2024 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI);2024-03-14

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