Multi-scale object detection based on attention mechanism

Shenshen Sun; Xue Bao; Xirui Wang

doi:10.1117/12.3023975

14 February 2024 Multi-scale object detection based on attention mechanism

Shenshen Sun, Xue Bao, Xirui Wang

Proceedings Volume 13018, International Conference on Smart Transportation and City Engineering (STCE 2023); 130185Q (2024) https://doi.org/10.1117/12.3023975
Event: International Conference on Smart Transportation and City Engineering (STCE 2023), 2023, Chongqing, China

Abstract

In order to solve the problem of missing target detection in traffic road target detection task due to excessive change of target scale in complex environment. An improved object detection method based on YOLOv5 is proposed, which introduces Coordinate Attention (CA), it fuses the coordinate attention mechanism into the last layer of the backbone network C3 module and the Bottleneck module in the C3 module to enhance the feature extraction ability of the target. The experimental results show that the vehicle detection accuracy of the fusion model reaches 96.5% on KITTI data set. Compared with other models, it can effectively improve the problem that the target scale of traffic road changes greatly.

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

Citation Download Citation

Shenshen Sun, Xue Bao, and Xirui Wang "Multi-scale object detection based on attention mechanism", Proc. SPIE 13018, International Conference on Smart Transportation and City Engineering (STCE 2023), 130185Q (14 February 2024); https://doi.org/10.1117/12.3023975

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KEYWORDS

Object detection

Target detection

Data modeling

Detection and tracking algorithms

Computer vision technology

Feature extraction

Performance modeling

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