DeepLeaf: Revolutionizing Rice Disease Detection and Classification using Convolutional Neural Networks and Random Forest Hybrid Model-Reference-Cited by-同舟云学术

DeepLeaf: Revolutionizing Rice Disease Detection and Classification using Convolutional Neural Networks and Random Forest Hybrid Model

Published:2023-07-06 Issue: Volume: Page:
ISSN:
Container-title:2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
language:
Short-container-title:

Author:

Kukreja Vinay¹,Sharma Rishabh¹,Vats Satvik²,Manwal Manika³

Affiliation:

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

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

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

Publisher

IEEE

Link

Reference16 articles.

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

2. Enhancing Human Resource Management through Deep Learning: A Predictive Analytics Approach to Employee Retention Success;2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS);2024-06-28

4. Enhancing Green Bean Anthracnose Severity Detection via Integrated CNN-LSTM Models;2023 4th International Conference on Intelligent Technologies (CONIT);2024-06-21

5. Enhancing Rice Crop Health Assessment: Evaluating Disease Identification with a CNN-RF Hybrid Approach;2024 International Conference on Innovations and Challenges in Emerging Technologies (ICICET);2024-06-07