Year: 2019
Type: article
Abstract: While reducing reliance on experts, automatic species identification can provide strong technical assistance to ecological environment monitoring, biodiversity protection, pest control. However, all the datasets used for butterfly species auto-identification are currently based on specimen images, and there is a lack of ecological butterfly images. Therefore, we set up a dataset of butterfly images which includes ecological images of the butterfly species in China, corresponding annotation files in PASCAL VOC 2007 format, and a mask for each image. The dataset contains 721 butterfly images, covering 94 butterfly species. Each annotation file corresponds to an image, which contains the image size, taxonomic information and location of the butterfly. The mask file for each image corresponds to the specific location of the butterfly in the image. This dataset can support researches on automatic butterfly species recognition, object detection, image segmentation and insect taxonomy.
Source: China Scientific Data
Authors: Juanying Xie, Jiawen Cao, Libin Ma, Wenquan Zhen, Zhenning Chen, Xiaodong Li, Houhun Li, Shengquan Xu
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4403737350