Jute Health Decoded: Severity Level Analysis Through Federated Learning CNN-Reference-Cited by-同舟云学术

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Jute Health Decoded: Severity Level Analysis Through Federated Learning CNN

Published:2023-12-22 Issue: Volume: Page:203-209
ISSN:
Container-title:2023 12th International Conference on System Modeling & Advancement in Research Trends (SMART)
language:
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Author:

Bansal Ankit¹,Vats Satvik²,Prasad Chandan³,Kukreja Vinay¹,Mehta Shiva¹

Affiliation:

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

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

3. JSPM Rajarshi Shahu College of Engineering,Pune,Maharashtra

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10428119/10428128/10428487.pdf?arnumber=10428487

Reference17 articles.

1. Evaluating the Potential of Federated Learning for Maize Leaf Disease Prediction

2. Recognizing Wheat Aphid Disease Using a Novel Parallel Real-Time Technique Based on Mask Scoring RCNN

3. A Federated Learning CNN Approach for Tomato Leaf Disease with Severity Analysis

4. Next-Generation Wheat Disease Monitoring: Leveraging Federated Convolutional Neural Networks for Severity Estimation

5. Design and Evaluation of a PBL-Based Course in Analog Electronics

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