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Frontiers in Signal Processing
FSP > Volume 5, Number 1, January 2021

Road Object Detection of YOLO Algorithm with Attention Mechanism

Download PDF  (844.2 KB)PP. 9-16,  Pub. Date:January 13, 2021
DOI: 10.22606/fsp.2021.51002

Author(s)
Jiacheng Li, Huazhang Wang, Yuan Xu, Fan Liu
Affiliation(s)
College of Electrical Engineering, Southwest Minzu University, Chengdu, China
College of Electrical Engineering, Southwest Minzu University, Chengdu, China
College of Electrical Engineering, Southwest Minzu University, Chengdu, China
College of Electrical Engineering, Southwest Minzu University, Chengdu, China
Abstract
In auto-driving cars, incorrect object detection can lead to serious accidents, so high-precision object detection is the key to automatic driving. This paper improves on the YOLOv3 object detection algorithm, and introduces the channel attention mechanism and spatial attention mechanism into the feature extraction network, which is used to autonomously learn the weight of each channel, enhance key features, and suppress redundant features. Experimental results show that the detection effect of the improved network algorithm is significantly higher than that of the YOLOv3 algorithm.
Keywords
autonomous driving, object detection, YOLOv3, channel attention mechanism, spatial attention mechanism
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