JOURNAL ARTICLE

Road Object Detection of YOLO Algorithm with Attention Mechanism

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:
Computer science Object detection Object (grammar) Artificial intelligence Key (lock) Mechanism (biology) Channel (broadcasting) Feature extraction Feature (linguistics) Computer vision Pattern recognition (psychology) Computer network Computer security

Metrics

9
Cited By
0.92
FWCI (Field Weighted Citation Impact)
16
Refs
0.75
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Neural Network Applications
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Autonomous Vehicle Technology and Safety
Physical Sciences →  Engineering →  Automotive Engineering
Industrial Vision Systems and Defect Detection
Physical Sciences →  Engineering →  Industrial and Manufacturing Engineering
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