Food Image Recognition Based on Densely Connected Convolutional Neural Networks

Al Selwi Metwalli, Wei Shen, Chase Q. Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Convolutional neural networks have been widely used for image recognition as they are capable of extracting features with high accuracy. In this paper, we propose a DenseFood model based on densely connected convolutional neural network architecture, which consists of multiple layers. A combination of softmax loss and center loss is used during the training process to minimize the variation within the same category and maximize the variation across different ones. For performance comparison, three models, namely, DenseFood, DenseNet121, and ResNet50 are trained using VIREO-172 dataset. In addition, we fine tune pre-trained DenseNet121 and ResNet50 models to extract features from the dataset. Experimental results show that the proposed DenseFood model achieves an accuracy of 81.23% and outperforms the other models in comparison.

Original languageEnglish (US)
Title of host publication2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages27-32
Number of pages6
ISBN (Electronic)9781728149851
DOIs
StatePublished - Feb 2020
Externally publishedYes
Event2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 - Fukuoka, Japan
Duration: Feb 19 2020Feb 21 2020

Publication series

Name2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020

Conference

Conference2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
CountryJapan
CityFukuoka
Period2/19/202/21/20

All Science Journal Classification (ASJC) codes

  • Information Systems and Management
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Signal Processing

Keywords

  • Food image recognition
  • convolutional neural networks
  • deep learning
  • image classification

Fingerprint Dive into the research topics of 'Food Image Recognition Based on Densely Connected Convolutional Neural Networks'. Together they form a unique fingerprint.

Cite this