A Deep Learning Approach to Detect and Classify Wheat Leaf Spot Using Faster R-CNN and Support Vector Machine
Author:
Affiliation:
1. Chitkara University,Chitkara University Institute of Engineering and Technology,Punjab,India
2. GraphicEra Hill University,Dehradun
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10126131/10126116/10126124.pdf?arnumber=10126124
Reference15 articles.
1. Computer Vision Framework for Wheat Disease Identification and Classification Using Jetson GPU Infrastructure
2. N-CNN Based Transfer Learning Method for Classification of Powdery Mildew Wheat Disease
3. Multiple classifier combination for recognition of wheat leaf diseases;tian;Intell Autom Soft Comput,2011
4. An implementation and analysis of models for the detection of wheat rust disease;sood;International Conference on Intelligent Sustainable Systems,2020
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