Vehicle Detection Based on Improved Yolov11 and Attention Mechanism

In this paper, an improved vehicle detection method based on YOLOv11 and an attention mechanism is proposed. By optimizing the network structure and integrating the attention mechanism, the accuracy and efficiency of vehicle detection are significantly enhanced. The experimental results show that the proposed method outperforms the traditional YOLOv11 in various scenarios, providing a more reliable solution for intelligent transportation systems and related fields

Publication Details

Journal
PhilPapers (PhilPapers Foundation)
Published
2025-01-01
Primary Topic
Advanced Neural Network Applications
Type
article
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article

Vehicle Detection Based on Improved Yolov11 and Attention Mechanism

PhilPapers (PhilPapers Foundation)
Advanced Neural Network Applications
article

Vehicle Detection Based on Improved Yolov11 and Attention Mechanism

article en

Abstract

In this paper, an improved vehicle detection method based on YOLOv11 and an attention mechanism is proposed. By optimizing the network structure and integrating the attention mechanism, the accuracy and efficiency of vehicle detection are significantly enhanced. The experimental results show that the proposed method outperforms the traditional YOLOv11 in various scenarios, providing a more reliable solution for intelligent transportation systems and related fields

PhilPapers (PhilPapers Foundation)
Openalex Percentile: Top 47%
Advanced Neural Network Applications
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Vehicle Detection Based on Improved Yolov11 and Attention Mechanism · PhilPapers (PhilPapers Foundation) (2025) | TGRS Research Map | TGRS