SibNet: Food instance counting and segmentation

• Main Authors: NGUYEN, Huu-Thanh., NGO, Chong-wah, CHAN, Wing-Kwong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Food counting; Food instance segmentation; Artificial Intelligence and Robotics; Databases and Information Systems; Food Science
• Online Access: https://ink.library.smu.edu.sg/sis_research/6952; https://ink.library.smu.edu.sg/context/sis_research/article/7955/viewcontent/SibNet_av.pdf
• Institution: Singapore Management University

Food computing has recently attracted considerable research attention due to its significance for health risk analysis. In the literature, the majority of research efforts are dedicated to food recognition. Relatively few works are conducted for food counting and segmentation, which are essential fo...