딥러닝을 이용한 증강현실 기반 음료정보 시각화 및 공유 시스템

Forests play a key role in sustainable Earth. In terms of agricultural fields, forests prevent soil erosion by slowing water movement. Also, forests provide us a wide range of resources, such as wood, paper, and fruits. Even forests fight climate changes by absorbing greenhouse gases. Therefore, it is very significant for us to manage forests to preserve it. One of main issues concerning forest management is monitoring of health and growth of trees against forest pests and diseases. Forest pests and diseases are forestry problems caused by insects and pathogens, primarily fungi in trees. All parts of a tree can become infected, leading to decreases in wood quality, productivity and occasionally death. This paper presents a comprehensive brief review for machine learning-based approaches for the prediction of forest pests and diseases. In the paper, we introduce some noticeable cases for classifying and detecting infected trees from aerial images in some major researches on forest pests and disease.