An Automated System for Detecting Rice Crop Disease using CNN Inception V3 Transfer Learning Algorithm
Author:
Affiliation:
1. Sathyabama Institute of Science and Technology,Department of Computer Science and Engineering,Chennai,India
2. Sathyabama Institute of Science and Technology,Department of Electricals and Electronics Engineering,Chennai,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9741824/9741825/09742999.pdf?arnumber=9742999
Reference20 articles.
1. Diagnosis and recognition of grape leaf diseases: An automated system based on a novel saliency approach and canonical correlation analysis based multiple features fusion
2. Identification of tea leaf diseases by using an improved deep convolutional neural network
3. Smart Farming: Pomegranate Disease Detection Using Image Processing
4. Remote Sensing and Precision Agriculture Technologies for Crop Disease Detection and Management with a Practical Application Example
5. An effective automatic system deployed in agricultural Internet of Things using Multi-Context Fusion Network towards crop disease recognition in the wild
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1. Deep Learning-Based Classification of Wheat Leaf Diseases for Edge Devices;2023 2nd International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE);2023-11-27
2. Crop Disease Prediction Using Deep Learning Algorithms;Advances in Environmental Engineering and Green Technologies;2023-11-24
3. Identification of rice leaf diseases and deficiency disorders using a novel DeepBatch technique;Open Life Sciences;2023-01-01
4. Evaluation of Rice Degree of Milling Based on Bayesian Optimization and Multi-Scale Residual Model;Foods;2022-11-19
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