چکیده مقاله
This study introduces an innovative approach to classifying various types of Persian rice using image based deep learning techniques, highlighting the practical application of everyday technology in food categorization Recognizing the diversity of Persian rice and its culinary significance, we leveraged the capabilities of convolutional neural networks CNNs , specifically by fine tuning a ResNet model for accurate identification of different rice varieties and employing a U Net architecture for precise segmentation of rice grains in bulk images This dual methodology framework allows for both individual grain classification and comprehensive analysis of bulk rice samples, addressing two crucial aspects of rice quality assessment Utilizing images captured with consumer grade cell phones reflects a realistic scenario in which individuals can leverage this technology for assistance with grocery shopping and meal preparation The dataset, comprising various rice types photographed under natural conditions without professional lighting or equipment, presents a challenging yet practical classification problem Our findings demonstrate the feasibility of using non professional images for food classification and the potential of deep learning models, like ResNet and U Net, to adapt to the nuances of everyday objects and textures This study contributes to the field by providing insights into the applicability of image based deep learning in daily life, specifically for enhancing consumer experiences and knowledge in food selection Furthermore, it opens avenues for extending this approach to other food categories and practical applications, emphasizing the role of accessible technology in bridging the gap between sophisticated computational methods and everyday tasks
کلیدواژهها
نویسندگان
Amin Saeidi Kelishami
Department of Computer Engineering Sharif University of Technology Tehran, Iran
Mahmood Saeedi Kelishami
Department of Mathematics Rasht Branch, Islamic Azad University Rasht, Iran
Sajjad Saeedi Kelishami
Department of Architecture Rasht Branch, Islamic Azad University Rasht, Iran
شیوه ارجاع
Saeidi Kelishami, Amin and Saeedi Kelishami, Mahmood and Saeedi Kelishami, Sajjad,1403,Cell Phone Image-Based Persian Rice Detection and Classification Using Deep Learning Techniques,The 10th International Conference on Industrial and Systems Engineering,Mashhad
ارائهشده در
مجموعه مقالات دهمین کنفرانس بین المللی مهندسی صنایع و سیستم ها28 شهریور 1403 · مشهد