A rigorous comparative analysis of deep learning models, specifically U-Net, Mask R-CNN, and YOLOv8-Seg, for real-time traffic sign segmentation shows that YOLOv8-Seg achieves an optimal trade-off with a mean Average Precision and experimental results indicate that YOLOv8-Seg achieves an optimal trade-off.
A rigorous comparative analysis of deep learning models, specifically U-Net, Mask R-CNN, and YOLOv8-Seg, for real-time traffic sign segmentation is presented, finding that YOLOv8-Seg achieves an optimal trade-off with a mean Average Precision.
Anaxon Muqimova· Techscience uz - Topical Iss...· 0 citations
Autonomous vehicle perception systems predominantly use red-green-blue (RGB) cameras, which experience significant performance degradation under adverse lighting conditions, with detection accuracy declining by 35–45% at night and in inclement weather. This limitation poses substantial safety risks for practical autono...
M. S. Al Jabbar, Silmi Ath Thahirah Al Azhima, A. S. Satyawan et al.· Jurnal Nasional Teknik Elekt...· 0 citations
Optical vision is a crucial part of self-driving cars. Vehicle, street, building, pedestrian, and road sign detection that is accurate could help self-driving cars drive as safely as human beings. Object detection, on the other hand, has been a tough task for years due to the effects of lighting, topology, and occlusio...
Anwar Ghani· International Journal of Com...· 0 citations
A streamlined vehicle detection framework that combines background subtraction for motion-oriented foreground extraction with a Haar cascade classifier for object identification in traffic video sequences is introduced, suggesting that classical computer vision techniques remain viable alternatives for real-time traffi...
Ni Gusti Ayu Dasriani, Anthony Anggrawan, Khasnur Hidjah et al.· International Journal of Inf...· 0 citations
Efficient and accurate object detection is a cornerstone of computer vision applications,
particularly in autonomous driving systems where real-time performance is paramount. This
study revisits the fundamental challenge of balancing detection speed and accuracy, a critical
trade-off that has defined the evolution o...
Chima Igiri Godknows· International Journal of Com...· 0 citations
This work systematically evaluates the proposed approach on aerial RGB images from a public dataset as well as on noisy depth images captured onboard a drone using a lightweight depth camera, showing that the ViT-based model consistently outperforms widely used CNN architectures, including ResNet, particularly in low-d...
Victoria Eugenia Vazquez-Meza, J. Martínez-Carranza· Unmanned Systems· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
