2026-10-14T07:34:31Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33733090 2026-09-14T13:45:33Z category_28879 item_type_3 month_year_09_2026

UB-SOD dataset for small UAV and bird detection in airport low-altitude surveillance Shanliang Liu (13122417) Xiaoyang Jia (24876487) Guangshuai Gao (20225391) Shuxian Ma (5223617) Yiran Bie (24879368) Jiangang Wang (24879857) Computer vision UAV Detection bird detection Small Object Detection airport surveillance low-altitude airspace computer vision aviation safety <p dir="ltr">UB-SOD is a real-world image dataset developed for small UAV and bird detection in low-altitude airport surveillance environments.</p><p><br></p><p dir="ltr">The dataset contains 7,118 JPG images and 18,042 manually annotated object instances, including 10,047 UAV instances and 7,995 bird instances.</p><p><br></p><p dir="ltr">The images were collected from approximately 32 airport environments, covering diverse backgrounds and environmental conditions. Bounding-box annotations are provided in YOLO TXT, Pascal VOC XML, and COCO JSON formats. Fixed training, validation, and test splits are included.</p><p><br></p><p dir="ltr">According to the COCO object-area definition, 13,288 annotated instances (73.65%) belong to the small-object category, 3,810 (21.12%) to the medium-object category, and 944 (5.23%) to the large-object category.</p><p><br></p><p dir="ltr">The dataset is intended to support research on small-object detection, UAV and bird discrimination, airport low-altitude surveillance, and related computer vision tasks.</p> 2026-09-14T13:45:33Z Dataset Dataset 10.6084/m9.figshare.33733090.v1 https://figshare.com/articles/dataset/UB-SOD_dataset_for_small_UAV_and_bird_detection_in_airport_low-altitude_surveillance/33733090 CC BY 4.0