Kai-Rong ChangTsung-Hsiang MaYan-Fu Kuo2024-11-192024-11-192023https://www.scopus.com/record/display.uri?eid=2-s2.0-85207988610&origin=resultslisthttps://scholars.lib.ntu.edu.tw/handle/123456789/723135Food production is an increasingly important topic worldwide due to factors such as population increase and workforce aging. In conventional agriculture, which consists of forestry, fishery, and agriculture, and animal husbandry, manual observation is the main method used by farmers to monitor field and animal conditions. However, the younger generation is reluctant to engage in farming due to the high labor requirements and low wages. To solve this problem, smart machine vision, which is the combination of deep learning and machine vision, is applied for managing farms and increasing production. In this section, the architectures of smart machine vision applications are highlighted. Several examples of the applications are shown.falseArtificial intelligenceConvolutional neural networksDeep learningFood securityMachine learningRecurrent neural networks[SDGs]SDG2[SDGs]SDG14book part10.1007/978-981-19-8113-5_82-s2.0-85207988610