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Session Ⅱ: Medical AI

A novel plant disease recognition pipeline using object detection and image retrieval

첫 페이지 보기
  • 발행기관
    한국차세대컴퓨팅학회 바로가기
  • 간행물
    한국차세대컴퓨팅학회 학술대회 바로가기
  • 통권
    The 9th International Conference on Next Generation Computing 2023 (2023.12)바로가기
  • 페이지
    pp.93-96
  • 저자
    Helin Yin, Dong Jin, Ri Zheng, Ji-Min Lee, Yeong Hyeon Gu
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A448126

원문정보

초록

영어
Crop diseases and pests are one of the agricultural disasters that adversely affect the yield and quality of crops. To prevent and control them, many researchers have been working on deep learning-based disease and pest recognition. Most of these studies use classification techniques to output one class with the highest probability from a predefined list of pests. However, the accuracy of classification models is not perfect, and they can produce enough incorrect results to require additional aids. In this study, we proposed a novel disease and pest diagnosis pipeline that combines object detection with a similarity-based retrieval model. In our proposed pipeline, we first detect the damaged region in the image and then classify the class to which it belongs. In the similarity-based retrieval model, the detected region image can be used to further show the user the most similar damage symptom images to help them make a final decision. The pipeline proposed in this study was first applied to three diseases: fire blight, scab, and black necrotic leaf spot.

목차

Abstract
I. INTRODUCTION
II. RELATED WORK
III. PROPOSED PIPELINE
A. Dataset
B. Proposed plant disease diagnostic pipeline
IV. EXPERIMENTAL RESULTS
A. Performance of disease detection models
B. Performance of similarity-based image retrieval models
C. Expected scenarios
V. CONCLUSIONS
ACKNOWLEDGMENT
REFERENCES

키워드

classification fire blight object detection plant disease similarity-based retrieval

저자

  • Helin Yin [ Department of Artificial Intelligence Sejong University ]
  • Dong Jin [ Department of Computer Science and Engineering Department of Convergence Engineering for Intelligent Drone Sejong University ]
  • Ri Zheng [ Department of Computer Science and Engineering Department of Convergence Engineering for Intelligent Drone Sejong University ]
  • Ji-Min Lee [ Department of Computer Science and Engineering Department of Convergence Engineering for Intelligent Drone Sejong University ]
  • Yeong Hyeon Gu [ Department of Artificial Intelligence Sejong University ] Corresponding author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국차세대컴퓨팅학회 [Korean Institute of Next Generation Computing]
  • 설립연도
    2005
  • 분야
    공학>컴퓨터학
  • 소개
    본 학회는 차세대 PC 및 그 관련분야의 학술활동을 통하여 차세대 PC의 학문 및 기술발전을 도모하고 산업발전 및 국제협력 증진을 목적으로 한다.

간행물

  • 간행물명
    한국차세대컴퓨팅학회 학술대회
  • 간기
    반년간
  • 수록기간
    2021~2025
  • 십진분류
    KDC 566 DDC 004

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