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 language | English |
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Title of host publication | 11th International Conference on Information and Communication Technology, ICoICT 2023 |
Editors | Lee-Ying Chong, Tee Connie, Dawam Dwi Jatmiko Suwawi, Joon Liang Tan |
Place of Publication | Piscataway NJ USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 283-288 |
Number of pages | 6 |
ISBN (Electronic) | 9798350321982 |
ISBN (Print) | 9798350333039 |
DOIs | |
Publication status | Published - 2023 |
Externally published | Yes |
Event | International Conference on Information and Communication Technology 2023 - Melaka, Malaysia Duration: 23 Aug 2023 → 24 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
Conference | International Conference on Information and Communication Technology 2023 |
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Abbreviated title | ICoICT 2023 |
Country/Territory | Malaysia |
City | Melaka |
Period | 23/08/23 → 24/08/23 |
Internet address |
Keywords
- Faster Region-Based Convolutional Neural Networks (Faster R-CNN)
- Food detection
- Object detection
- YOLOv5