A survey of object detection based on deep learning

Wei Jiang; Zichao Zhang; Qian Xiong; Bo Yang

doi:10.1117/12.3049936

8 November 2024 A survey of object detection based on deep learning

Wei Jiang, Zichao Zhang, Qian Xiong, Bo Yang

Proceedings Volume 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024); 134161U (2024) https://doi.org/10.1117/12.3049936
Event: 2024 4th International Conference on Advanced Algorithms and Neural Networks, 2024, Qingdao, China

Abstract

Identifying and pinpointing objects within images or videos is a core objective in the field of computer vision, known as object detection. This study delves into the most recent advancements in object detection, with an emphasis on four primary approaches: Two-Stage Detectors, One-Stage Detectors, Anchor-Free Detectors, and Transformer-based Detectors. Each approach possesses distinct strengths and weaknesses, and the selection is dictated by the specific needs of the application. As research progresses, the techniques for object detection are advancing in precision and efficiency, while also expanding their ability to manage a wide array of object categories and scenarios. These advancements are pivotal in numerous domains, such as autonomous vehicles, security monitoring, and medical diagnostics.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Wei Jiang, Zichao Zhang, Qian Xiong, and Bo Yang "A survey of object detection based on deep learning", Proc. SPIE 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024), 134161U (8 November 2024); https://doi.org/10.1117/12.3049936

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