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Food Image Classification and Nutrition Detection Using CNN
Subject area: Science,Engineering and Technology · Area of research: Information Technology
Abstract
Deep learning and the availability of greater datasets and computational resources have made classification more straightforward. In recent years, the convolutional neural network has become the most commonly used and popular image categorization approach. In this paper, various transfer learning approaches are used to classify images from an Indian cuisine dataset. Food plays a significant role in human life because it supplies us with a variety of nutrients, so it is crucial for everyone to keep track of their eating habits. As a result, food classification is a must for a better way of living. Pretrained models are employed in this project instead of typical ways of developing a model from the ground up, which saves computing time and money while also producing superior results. Dataset for Indian cuisine.
Keywords
Indian Food, Machine Learning, Food Image Classification
References
[1] David J. Attokaren, Ian G. Fernandes, A. Sriram, Y.V. Srinivasa Murthy, and Shashidhar G. Koolagudi, “Food Classification from Images Using Convolutional Neural Networks”, 2017.
[2] Bappaditya Mandal, N. B. Puhan and Avijit Verma, “Deep Convolutional Generative Adversarial Network Based Food Recognition Using Partially Labeled Data”, 2018.
[3] Heng Zhao, Kim-Hui Yap, Alex C. Kot , Lingyu Duan , Ngai-Man Cheung, “Few-shot and Many- shot Fusion Learning in Mobile Visual Food Recognition”, 2018.
How to cite this paper
@article{1703407,
author = {Aarati Shankar Survase, Kimaya Sawant, Rinal Lokhande, Srushti Pawar, Prof. Prajwali Korde},
title = {Food Image Classification and Nutrition Detection Using CNN},
journal = {Iconic Research And Engineering Journals},
year = {2022},
volume = {5},
number = {11},
pages = {10-12},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/17034071.pdf},
abstract = {Deep learning and the availability of greater datasets and computational resources have made classification more straightforward. In recent years, the convolutional neural network has become the most commonly used and popular image categorization approach. In this paper, various transfer learning approaches are used to classify images from an Indian cuisine dataset. Food plays a significant role in human life because it supplies us with a variety of nutrients, so it is crucial for everyone to keep track of their eating habits. As a result, food classification is a must for a better way of living. Pretrained models are employed in this project instead of typical ways of developing a model from the ground up, which saves computing time and money while also producing superior results. Dataset for Indian cuisine.},
keywords = {Indian Food, Machine Learning, Food Image Classification},
month = {May},
}