AUTHOR=Liu Bing , Liu Luyang , Zhuo Ran , Chen Weidong , Duan Rui , Wang Guishen TITLE=A Dataset for Forestry Pest Identification JOURNAL=Frontiers in Plant Science VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2022.857104 DOI=10.3389/fpls.2022.857104 ISSN=1664-462X ABSTRACT=

The identification of forest pests is of great significance to the prevention and control of the forest pests' scale. However, existing datasets mainly focus on common objects, which limits the application of deep learning techniques in specific fields (such as agriculture). In this paper, we collected images of forestry pests and constructed a dataset for forestry pest identification, called Forestry Pest Dataset. The Forestry Pest Dataset contains 31 categories of pests and their different forms. We conduct several mainstream object detection experiments on this dataset. The experimental results show that the dataset achieves good performance on various models. We hope that our Forestry Pest Dataset will help researchers in the field of pest control and pest detection in the future.