Abstract:

Agricultural pests are important reasons affecting crop yield and quality. Aphid is an important group of agricultural pest. Detecting and counting aphids is an important link for early detection and management of this pest. With the development of information technology, many experts and scholars have conducted extensive research on the identification of agricultural pests using computer vision, and have made certain progress. High-quality and large-scale basic data often play a decisive role in the development of computer vision, but the lack of this kind of image data is one of the challenges faced by pest identification. Aphids have features such as small size, dense distribution, inter insect shelter, and multiple forms of same species. These features also pose a serious challenge for the detection and counting of aphids. This article provides a total of 6287 high-definition original images, including a dataset of 13 agricultural pests (aphids) including peach aphid, cotton aphid, and grain constrictor aphid, etc. These aphid images were collected using DSLR cameras in a natural field environment. In order to ensure the high quality and reliability of the data, these images are cleaned and organized by professional personnel, and identified and classified by experts in the field of plant protection. This dataset can provide a data foundation for recognition, detection, counting and classification of aphids.

Key words: aphid, computer vision, image data