A study of multi-task and region-wise deep learning for food ingredient recognition

• Main Authors: CHEN, Jingjing, ZHU, Bin, NGO, Chong-wah, CHUA, Tat-Seng, JIANG, Yu-Gang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Image recognition; Visualization; Phase frequency detectors; Image segmentation; Fish; Deep learning; Shape; Food images; Chinese food; ingredient recognition; deep learning; Artificial Intelligence and Robotics; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/6301; https://ink.library.smu.edu.sg/context/sis_research/article/7304/viewcontent/Jing_tran_2021.pdf
• Institution: Singapore Management University

Food recognition has captured numerous research attention for its importance for health-related applications. The existing approaches mostly focus on the categorization of food according to dish names, while ignoring the underlying ingredient composition. In reality, two dishes with the same name do...