An Advanced YOLOv5s Approach for Vehicle Detection Integrating Swin Transformer and SimAM in Dense Traffic Surveillance
Journal Title: Journal of Industrial Intelligence - Year 2024, Vol 2, Issue 1
Abstract
In the realm of high-definition surveillance for dense traffic environments, the accurate detection and classification of vehicles remain paramount challenges, often hindered by missed detections and inaccuracies in vehicle type identification. Addressing these issues, an enhanced version of the You Only Look Once version v5s (YOLOv5s) algorithm is presented, wherein the conventional network structure is optimally modified through the partial integration of the Swin Transformer V2. This innovative approach leverages the convolutional neural networks' (CNNs) proficiency in local feature extraction alongside the Swin Transformer V2's capability in global representation capture, thereby creating a symbiotic system for improved vehicle detection. Furthermore, the introduction of the Similarity-based Attention Module (SimAM) within the CNN framework plays a pivotal role, dynamically refocusing the feature map to accentuate local features critical for accurate detection. An empirical evaluation of this augmented YOLOv5s algorithm demonstrates a significant uplift in performance metrics, evidencing an average detection precision (mAP@0.5:0.95) of 65.7%. Specifically, in the domain of vehicle category identification, a notable increase in the true positive rate by 4.48% is observed, alongside a reduction in the false negative rate by 4.11%. The culmination of these enhancements through the integration of Swin Transformer and SimAM within the YOLOv5s framework marks a substantial advancement in the precision of vehicle type recognition and reduction of target miss detection in densely populated traffic flows. The methodology's success underscores the efficacy of this integrated approach in overcoming the prevalent limitations of existing vehicle detection algorithms under complex surveillance scenarios.
Authors and Affiliations
Yi Zhang, Zheng Sun
Keywords
Related Articles
- EP ID EP743948
- DOI 10.56578/jii020103
- Views 43
- Downloads 0
Fuzzy Logic-Based Fault Detection in Industrial Production Systems: A Case Study
The burgeoning application of artificial intelligence (AI) technologies for the diagnosis and detection of defects has marked a significant area of interest among researchers in recent years. This study presents a fuzzy...
Numerical Analysis of Two-Phase Flow in Serrated Minichannels Using COMSOL Multiphysics
In the realm of engineering, the significance of minichannels has escalated, especially in micro-scale multiphase fluid dynamics. This study conducts an extensive numerical analysis of two-phase flow in minichannels, uti...
Aerodynamic Performance of High-Speed Maglev Trains Under Crosswind Conditions: A Computational Simulation Study
In the realm of ground transportation, high-speed maglev trains stand out due to their exceptional stability, rapid velocity, and environmental benefits, such as low pollution and noise. However, the aerodynamic challeng...
Intuitionistic Fuzzy Multi-Index Multi-Criteria Decision-Making for Smart Phone Selection Using Similarity Measures in a Fuzzy Environment
Smart phone selection involves several product attributes and brand values of the manufacturing company, and the sets of alternatives, criteria, and decision-makers may be updated multiple times during the purchasing pro...
Enhancing Multi-Attribute Decision Making with Pythagorean Fuzzy Hamacher Aggregation Operators
The attention of many researchers has been drawn to Pythagorean fuzzy information, which involves Pythagorean fuzzy numbers and their aggregation operators. In this study, the concept of the Pythagorean fuzzy set is disc...