Machine Learning Techniques for Tomato Plant Diseases Clustering, Prediction and Classification-Reference-Cited by-同舟云学术

Machine Learning Techniques for Tomato Plant Diseases Clustering, Prediction and Classification

Published:2021-11 Issue: Volume: Page:
ISSN:
Container-title:2021 International Conference on Promising Electronic Technologies (ICPET)
language:
Short-container-title:

Author:

Qasrawi Radwan,Amro Malak,Zaghal Raid,Sawafteh Mohammad,Polo Stephanny Vicuna

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9691501/9692003/09692066.pdf?arnumber=9692066

Reference32 articles.

1. A review on machine learning techniques for rice plant disease detection in agricultural research;daniya;Int J Adv Sci Technol,2019

2. Machine Learning for Plant Leaf Disease Detection and Classification – A Review

3. Comparative Study of Different Orange Data Mining Tool-Based AI Techniques in Image Classification

4. Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features;arivazhagan;Agric Eng Int CIGR Journal,2013

5. Data Mining Approach to the Detection of Suicide in Social Media: A Case Study of Singapore

Cited by 6 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

1. Vision Transformers in Optimization of AI-Based Early Detection of Botrytis cinerea;AI;2024-08-01

2. Smartphone-Based Citizen Science Tool for Plant Disease and Insect Pest Detection Using Artificial Intelligence;Technologies;2024-07-03

3. Machine Learning Techniques for Detection and Classification of Crop (Solanum lycopersicum) Plant Diseases Due to Pests: A Review;Lecture Notes in Electrical Engineering;2024

4. Revolutionizing Agriculture through Leaf Disease Prediction in Plants;2023 Global Conference on Information Technologies and Communications (GCITC);2023-12-01

5. Detection of Botrytis Cinerea in Grapes using Machine Learning Technique;2023 International Conference on Evolutionary Algorithms and Soft Computing Techniques (EASCT);2023-10-20