1. GooseDetectlion: A Fully Annotated Dataset for Lion-head Goose Detection in Smart Farms.
- Author
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Feng, Yuhong, Li, Wen, Guo, Yuhang, Wang, Yifeng, Tang, Shengjun, Yuan, Yichen, and Shen, Linlin
- Subjects
FARM mechanization ,ARTIFICIAL intelligence ,DETECTORS ,GEESE ,VOLUNTEERS ,LIONS - Abstract
Large datasets are required to develop Artificial Intelligence (AI) models in AI powered smart farming for reducing farmers' routine workload, this paper contributes the first large lion-head goose dataset GooseDetect
lion , which consists of 2,660 images and 98,111 bounding box annotations. The dataset was collected with 6 cameras deployed in a goose farm in Chenghai district of Shantou city, Guangdong province, China. Images sampled from videos collected during July 9 -10 in 2022 were fully annotated by a team of fifty volunteers. Compared with another 6 well known animal datasets in literature, our dataset has higher capacity and density, which provides a challenging detection benchmark for main stream object detectors. Six state-of-the-art object detectors have been selected to be evaluated on the GooseDetectlion , which includes one two-stage anchor-based detector, three one-stage anchor-based detectors, as well as two one-stage anchor-free detectors. The results suggest that the one-stage anchor-based detector You Only Look Once version 5 (YOLO v5) achieves the best overall performance in terms of detection precision, model size and inference efficiency. [ABSTRACT FROM AUTHOR]- Published
- 2024
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