JOURNAL ARTICLE

Food Image Classification with Convolutional Neural Network

Abstract

In our paper we tried to classify food images using convolutional neural network. Convolutional neural network extracts spatial features from images so it is very efficient to use convolutional neural network for image clasification problem. Recently people are sharing food images in social media and writing review on food. So there is a lot of food image in the social media but some image may not be labeled. It will be very helpful for restaurants if they can advertise their food to those people who is looking similar kind of foods they offer. Food classification system can help social media platform to identify food. Food classification system can enable an opportunity for social media platform to offer advertisement service for restaurants and beverage companies to their targeted users. It will be financially beneficial for both social media platform and beverage companies. Food classification is very difficult task because there is high variance in same category of food images. We developed a convolutional neural network model to classify food images in food-11 dataset. We also used a pre-trained Inception V3 convolutional neural network model to classify food images.

Keywords:
Convolutional neural network Computer science Artificial intelligence Social media Contextual image classification Artificial neural network Pattern recognition (psychology) Machine learning Image (mathematics) Computer vision World Wide Web

Metrics

51
Cited By
1.82
FWCI (Field Weighted Citation Impact)
22
Refs
0.83
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Chemical Sensor Technologies
Physical Sciences →  Engineering →  Biomedical Engineering
Nutritional Studies and Diet
Health Sciences →  Medicine →  Public Health, Environmental and Occupational Health
Culinary Culture and Tourism
Life Sciences →  Agricultural and Biological Sciences →  Food Science

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