Implementing CNN and RF Models for Multi-Level Classification: Deciphering Beetroot Aphid Disease Severity-Reference-Cited by-同舟云学术

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Implementing CNN and RF Models for Multi-Level Classification: Deciphering Beetroot Aphid Disease Severity

Published:2024-05-24 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 5th International Conference for Emerging Technology (INCET)
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Author:

Ojha Nitish Kumar¹,Upadhyay Deepak²,Manwal Manika³,Kukreja Vinay⁴,Sharma Rishabh⁴

Affiliation:

1. Computer Science and Application, IIMT University, Meerut,Uttar Pradesh,India

2. Computer Science and Engineering, Graphic Era Hill University,Dehradun,Uttarakhand,India,248002

3. Computer Science and Engineering, Graphic Era Deemed to be University,Dehradun,Uttrakhand,India

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

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592862/10592849/10593519.pdf?arnumber=10593519

Reference15 articles.

1. Deep learning-based detection of aphid colonies on plants from a reconstructed Brassica image dataset

2. Deep learning based automated disease detection and pest classification in Indian mung bean

3. Review on Leaf diseases detection using Deep learning

4. From identification to forecasting: the potential of image recognition and artificial intelligence for aphid pest monitoring

5. Optimized deep residual network system for diagnosing tomato pests

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