鉴定(生物学)
计算机科学
营养物
深度学习
人工智能
特征(语言学)
建筑
模式识别(心理学)
计算机视觉
生物
地理
生态学
语言学
哲学
植物
考古
作者
Chiun-Li Chin,Chen-Cheng Huang,Bing-Jhang Lin,Guei-Ru Wu,Tzu-Chieh Weng,Ho-Feng Chen
标识
DOI:10.1109/ifuzzy.2016.8004962
摘要
According to the similar nutritional properties, foods could be classified in six groups (Vegetables, Fruits, Dairy, Oils, Grains and Protein foods) and nourish human body respectively. However, people could not understand the nutrients of foods which they obtained generally. Hence, this paper proposes a system based on deep learning for training. Users take pictures on diets by their smartphones and the system will recognize both what kinds of group and how much of nutrients they will take in. With our system, users could recognize the nutrients in their diet and they can administer their health effectively. During training, we not only confirm the architecture of CNN, but also find out that the color feature of foods in the images has significant effect on the identification result about up to seventy percent of the resolution ratio.
科研通智能强力驱动
Strongly Powered by AbleSci AI