Application of computer vision in livestock and crop production—A review

Abstract

Nowadays, it is a challenge for farmers to produce healthier food for the world population and save land resources. Recently, the integration of computer vision technology in field and crop production ushered in a new era of innovation and efficiency. Computer vision, a subfield of artificial intelligence, leverages image and video analysis to extract meaningful information from visual data. In agriculture, this technology is being utilized for tasks ranging from disease detection and yield prediction to animal health monitoring and quality control. By employing various imaging techniques, such as drones, satellites, and specialized cameras, computer vision systems are able to assess the health and growth of crops and livestock with unprecedented accuracy. The review is divided into two parts: Livestock and Crop Production giving the overview of the application of computer vision applications within agriculture, highlighting its role in optimizing farming practices and enhancing agricultural productivity.

Plant phenotyping relevance

作物の健康状態・成長・病害・収量などを画像解析で評価するコンピュータビジョン応用をレビューしており、植物フェノタイピング手法のレビューが中心です。

Code and data availability

This is a review article on computer vision in livestock and crop production. It presents no original plant-phenotyping measurements, datasets, images, code, or models of its own; the data availability statement says 'Not applicable.' All referenced datasets (ImageNet, PASCAL VOC, MSCOCO, cattle datasets) and web URLs,

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