Hybrid CNN & Random Forest Model for Effective Ashwagandha Leaf Disease Diagnosis
Author:
Affiliation:
1. Chitkara University Institute of Engineering and Technology, Chitkara University,Punjab,India
2. Graphic Era Hill University,Dehradun,Uttarakhand,India,248002
3. Graphic Era Deemed to be University,Dehradun,Uttarakhand,India,248002
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10441789/10441802/10441839.pdf?arnumber=10441839
Reference17 articles.
1. An Optimized Deep Learning Model for Grassy Shoot Disease Prediction in Sugarcane
2. Red Rot Disease Prediction in Sugarcane Using the Deep Learning Approach
3. Predicting Tulip Leaf Diseases: A Integrated CNN and Random Forest Approach
4. A Random Forest-Based Leaf Classification Using Multiple Features
5. Role of Oxidative Stress and Inflammation in Insomnia Sleep Disorder and Cardiovascular Diseases: Herbal Antioxidants and Anti-inflammatory Coupled with Insomnia Detection using Machine Learning
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