Computer Vision-Based Intelligent Non-Destructive Testing for Fish Meat Quality Assessment: A Hybrid Convolutional Neural Network and Support Vector Machine Approach

چکیده مقاله

Ensuring food safety has historically been one of humanity's most significant challenges, often accompanied by considerable costs, time, and potential for errors The verification and classification of fish meat traditionally rely on destructive testing methods, such as physical and chemical tools, which present various problems and challenges Today, with the expanding application of artificial intelligence, it is possible to classify fish meat with high speed and accuracy Therefore, the aim of this research was to present a non destructive intelligent model for the classification and identification of fish meat into three classes: healthy, normal, and spoiled The dataset for modeling and analysis was collected from the Kaggle database, with each class containing 400 images This study analyzes and implements two deep learning based approaches for detecting fish freshness from images The first method involves training a Convolutional Neural Network CNN model using the Mobile NetV2 architecture with added dense layers In the second approach, Mobile NetV2 is utilized as a feature extractor, and then a Support Vector Machine SVM classifier is trained on the extracted features The results indicate that both approaches achieve acceptable accuracy, but the hybrid Mobile NetV2 SVM model demonstrates significantly superior performance in classifying fish freshness categories This study emphasizes the effectiveness of transfer learning and the advantage of using SVM for final classification in practical applications

کلیدواژه‌ها

نویسندگان

Seyd Vahab Shojaedini

Department of Electrical Engineering, Iranian Research Organization for Science and Technology, Tehran, Iran

Kia Abbasi

Department of Artificial Intelligence, Islamic Azad University of Electronic Campus, Tehran, Iran

Mostafa Heshmati

Department of Artificial Intelligence, Islamic Azad University of Electronic Campus, Tehran, Iran

Shojaedini, Seyd Vahab and Abbasi, Kia and Heshmati, Mostafa,1404,Computer Vision-Based Intelligent Non-Destructive Testing for Fish Meat Quality Assessment: A Hybrid Convolutional Neural Network and Support Vector Machine Approach,Ninth International Conference on Interdisciplinary Studies in Food industry and Nutrition Science of Iran,Tehran

ارائه‌شده در

مجموعه مقالات نهمین همایش بین المللی مطالعات میان رشته ای در صنایع غذایی و علوم تغذیه ایران29 آبان 1404 · تهران