Food Detection and Recognition with Deep Learning: A Comparative Study

Siao Wah Tan, Chin Poo Lee, Kian Ming Lim, Jit Yan Lim

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

3 Citations (Scopus)

Abstract

Food detection and recognition involves the use of computer vision and machine learning techniques to identify and classify food items in images or videos. It has numerous applications, such as dietary tracking, nutrition analysis, and inventory management. This research paper presents a comparative study of six deep learning models (SSD (VGG-16), Faster-RCNN (Resnet-50), Faster-RCNN (Mobilenet-V3), Faster-RCNN (Mobilenet-V3-320), RetinaNet (Resnet-50), and YOLOv5) for food detection and recognition. The models' performance is evaluated using three publicly available datasets: School Lunch Dataset, UEC FOOD 100, and UEC FOOD 256. Notably, Faster R-CNN (Mobilenet-V3) achieved mAP of 0.931 in the School Lunch Dataset, while YOLOv5 achieved 0.774 and 0.701 mAP in the UEC FOOD 100 and UEC FOOD 256 Datasets, respectively. YOLOv5 demonstrates comparable results to Faster R-CNN but with a smaller input image size and a larger batch size in food detection.

Original languageEnglish
Title of host publication11th International Conference on Information and Communication Technology, ICoICT 2023
EditorsLee-Ying Chong, Tee Connie, Dawam Dwi Jatmiko Suwawi, Joon Liang Tan
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages283-288
Number of pages6
ISBN (Electronic)9798350321982
ISBN (Print)9798350333039
DOIs
Publication statusPublished - 2023
Externally publishedYes
EventInternational Conference on Information and Communication Technology 2023 - Melaka, Malaysia
Duration: 23 Aug 202324 Aug 2023
Conference number: 11th
https://ieeexplore.ieee.org/xpl/conhome/10262402/proceeding (Proceedings)
https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&ved=2ahUKEwiKrtbNp-GEAxUbs1YBHZlDAVkQFnoECA8QAQ&url=https%3A%2F%2Fwww.icoict.org%2F2023-icoict%2F&usg=AOvVaw2TRUvwZYzGEHUrk65UNNeI&opi=89978449 (Website)

Conference

ConferenceInternational Conference on Information and Communication Technology 2023
Abbreviated titleICoICT 2023
Country/TerritoryMalaysia
CityMelaka
Period23/08/2324/08/23
Internet address

Keywords

  • Faster Region-Based Convolutional Neural Networks (Faster R-CNN)
  • Food detection
  • Object detection
  • YOLOv5

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