Prof. Zhihao Liao Profile

Prof. Zhihao Liao

at Nanchang Univ

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Proceedings Article | 15 October 2021 Paper

A bird species detection method based on YOLO-v5

Zhihao Liao, Ming Tian

Proceedings Volume 11933, 119330C (2021) https://doi.org/10.1117/12.2615310

KEYWORDS: Target detection, Detection and tracking algorithms, Data modeling, Evolutionary algorithms, Artificial intelligence, Target recognition, Speaker recognition, Neural networks, Neck, Intelligence systems

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The rapid development of image recognition technology has tremendously promoted the research of species detection. Detection of rare species has important implications for protecting biodiversity. This paper proposes a deep learning method to solve bird species detection based on the current powerful algorithm YOLO-v5. The algorithm combines the feature extraction network of CSPDarkNet to extract the feature information of the input bird image and then uses the aggregation network with a pyramid structure for detection to obtain the required semantic information. The experimental dataset comes from the Kaggle platform and is annotated with free software provided by Github. In this experiment, YOLO-v5 and the other five models are compared for the performance of bird species detection. The comparison results shown that YOLO-v5x has the best precision (95.36%) and mAP (91.28%). It can be seen that compared with other models, YOLO-v5x has high recognition accuracy, good robustness and can be better suited in the actual environment.

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