Journal of Korean Society for Quality Management (품질경영학회지)

Korean Society for Quality Management (한국품질경영학회)
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A Construction of Web Application Platform for Detection and Identification of Various Diseases in Tomato Plants Using a Deep Learning Algorithm

딥러닝 알고리즘을 이용한 토마토에서 발생하는 여러가지 병해충의 탐지와 식별에 대한 웹응용 플렛폼의 구축

  • Na, Myung Hwan (Department of Statistic, Chonnam National University) ;
  • Cho, Wanhyun (Department of Statistic, Chonnam National University) ;
  • Kim, SangKyoon (Department of Electronic Engineering, Mokpo National University)
  • Received : 2020.09.11
  • Accepted : 2020.11.25
  • Published : 2020.12.31
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Abstract

Purpose: purpose of this study was to propose the web application platform which can be to detect and discriminate various diseases and pest of tomato plant based on the large amount of disease image data observed in the facility or the open field. Methods: The deep learning algorithms uesed at the web applivation platform are consisted as the combining form of Faster R-CNN with the pre-trained convolution neural network (CNN) models such as SSD_mobilenet v1, Inception v2, Resnet50 and Resnet101 models. To evaluate the superiority of the newly proposed web application platform, we collected 850 images of four diseases such as Bacterial cankers, Late blight, Leaf miners, and Powdery mildew that occur the most frequent in tomato plants. Of these, 750 were used to learn the algorithm, and the remaining 100 images were used to evaluate the algorithm. Results: From the experiments, the deep learning algorithm combining Faster R-CNN with SSD_mobilnet v1, Inception v2, Resnet50, and Restnet101 showed detection accuracy of 31.0%, 87.7%, 84.4%, and 90.8% respectively. Finally, we constructed a web application platform that can detect and discriminate various tomato deseases using best deep learning algorithm. If farmers uploaded image captured by their digital cameras such as smart phone camera or DSLR (Digital Single Lens Reflex) camera, then they can receive an information for detection, identification and disease control about captured tomato disease through the proposed web application platform. Conclusion: Incheon Port needs to act actively paying.

Keywords

Acknowledgement

This work was supported by the Research Program of Rural Development Administration (Project No. PJ015337012020) and the Korea National Research Foundation (Project No. NRF-2020R1F1A1067066) of the Korea Grant funded by the Korean Government.

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