Food Image Classification with Convolutional Neural Network

被引:0
|
作者
Islam, Md Tohidul [1 ]
Siddique, B. M. Nafiz Karim [1 ]
Rahman, Sagidur [1 ]
Jabid, Taskeed [1 ]
机构
[1] East West Univ, Dept Comp Sci & Engn, Dhaka, Bangladesh
关键词
CNN; Computer Vision; Deep Learning; Image Recognition; Social Media; Food Image; Convolution Layer; Image Processing; Image Pre-Processing; MODEL;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:257 / +
页数:6
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