Research Article
Research on Disease Detection Systems in Tomato Plants using Artificial Intelligence
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 175 - Issue 36 |
| Published: Dec 2020 |
| Authors: Nguyen Le Dung, Tran Hau Van Toan |
10.5120/ijca2020920924
|
Nguyen Le Dung, Tran Hau Van Toan . Research on Disease Detection Systems in Tomato Plants using Artificial Intelligence. International Journal of Computer Applications. 175, 36 (Dec 2020), 24-29. DOI=10.5120/ijca2020920924
@article{ 10.5120/ijca2020920924,
author = { Nguyen Le Dung,Tran Hau Van Toan },
title = { Research on Disease Detection Systems in Tomato Plants using Artificial Intelligence },
journal = { International Journal of Computer Applications },
year = { 2020 },
volume = { 175 },
number = { 36 },
pages = { 24-29 },
doi = { 10.5120/ijca2020920924 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2020
%A Nguyen Le Dung
%A Tran Hau Van Toan
%T Research on Disease Detection Systems in Tomato Plants using Artificial Intelligence%T
%J International Journal of Computer Applications
%V 175
%N 36
%P 24-29
%R 10.5120/ijca2020920924
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This working personally discusses how to approach the Raspberry Pi 3B + Board in combination with the 8MP Raspberry Pi V2 camera, and at the same time about algorithm knowledge with the Raspberry Pi 3B + board, and also be able to communicate with reduction motors. V1 speed, RC servo motor, H bridge circuit. During the implementation of the individual use object detection method to perform identification and detection of tomato disease. Combine with a self-driving car with a camera to make it possible to sample tomato leaf disease in the most realistic way.
References
- Q. H. Cap, K. Suwa, E. Fujita, S. Kagiwada, H. Uga, H. Iyatomi, An End-To-End Practical Plant Disease Diagnosis System For Wide-Angle Cucumber Images, International Journal of Engineering & Technology, 2018, 106-111.
- Marko Arsenovic, Mirjana Karanovic, Srdjan Sladojevic, Darko Stefanovic, Solving Current Limitations of Deep Learning Based Approaches for Plant Disease Detection, 2019.
- Amanda Ramcharan, Peter McCloskey, Kelsee Baranowski, Neema Mbilinyi, Latifa Mrisho, Mathias Ndalahwa, James Legg, David P. Hughes, A Mobile-Based Deep Learning Model for Cassava Disease Diagnosis, 2019.
- Lalitpur, Dhapakhel, TOMATO PLANT DISEASES DETECTION SYSTEM USING IMAGE PROCESSING, 2018.
- Alexander Driaba, Volgograd, Recognition of Various Objects from a Certain Categorical Set in Real Time Using Deep Convolutional Neural Networks, 2019.
- Manhnh, HOW TO SELECT RIGHT DEEP LEARNING MODEL FOR OBJECT DETECTION APPLICATIONS, 2019.
- Chengwei, How to train an object detection model easy for free, 2019.
- Https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_model_zoo.md
- Https://www.kaggle.com/emmarex/plantdisease
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