학술논문

Detecting Fruit Diseases Using Deep Learning and Image Analysis
Document Type
Conference
Source
2023 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Computing, Communication, and Intelligent Systems (ICCCIS), 2023 International Conference on. :843-850 Nov, 2023
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Robotics and Control Systems
Deep learning
Training
Image segmentation
Computational modeling
Predictive models
Data models
Diseases
Fruits
CNN
Deep Learning
Machine Learning
Disease Detection
Language
Abstract
The implementation of several agriculture-related issues was made simple by advancements in computer vision technology. The detection of fruit diseases is one such issue. Using deep learning techniques, a lot of study has been done on many fruits, including apples, mangos, kiwis, passion fruit, and others. The most significant contributions made by this field in recent years are outlined in this review paper. In this review, we have performed a technical analysis of deep learning methods for predicting fruit illnesses. Along with the deep learning models utilized, the study also compares various picture acquisition, image pre-processing, and segmentation methods. The study discovered that the most accurate deep learning model can vary based on the system's computing capacity and the data used. In the article directions for future research have also been covered.