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Occlusion and multi-scale pedestrian detection A review
Array, 2023 Pedestrian detection has a wide range of application prospects in many fields such as unmanned driving, intelligent monitoring, robot, etc., and has always been a hot issue in the field of computer vision.
Wei Chen +4 more
doaj +3 more sources
A Pedestrian Detection Network Model Based on Improved YOLOv5. [PDF]
Entropy (Basel), 2023 Advanced object detection methods always face high algorithmic complexity or low accuracy when used in pedestrian target detection for the autonomous driving system.
Li ML, Sun GB, Yu JX.
europepmc +2 more sources
Pedestrian Detection Using Multispectral Images and a Deep Neural Network
Sensors, 2021 Pedestrian fatalities and injuries most likely occur in vehicle-pedestrian crashes. Meanwhile, engineers have tried to reduce the problems by developing a pedestrian detection function in Advanced Driver-Assistance Systems (ADAS) and autonomous vehicles.
Jason Nataprawira +3 more
doaj +3 more sources
Dense Pedestrian Detection Based on GR-YOLO. [PDF]
Sensors (Basel)In large public places such as railway stations and airports, dense pedestrian detection is important for safety and security. Deep learning methods provide relatively effective solutions but still face problems such as feature extraction difficulties ...
Li N +6 more
europepmc +2 more sources
International Journal of Scientific Research in Computer Science, Engineering and Information TechnologyIn an era of rapid urbanization and automation, pedestrian safety has become a central concern for surveillance and smart city infrastructure. This paper presents a lightweight yet efficient system for pedestrian detection using YOLOv4-tiny, optimized for real-time video analysis.
null Rajavel JM +3 more
semanticscholar +5 more sources
Robust pedestrian detection via constructing versatile pedestrian knowledge bank [PDF]
Pattern RecognitionPedestrian detection is a crucial field of computer vision research which can be adopted in various real-world applications (e.g., self-driving systems).
Sungjune Park +2 more
exaly +2 more sources
HRBUST-LLPED: A Benchmark Dataset for Wearable Low-Light Pedestrian Detection [PDF]
Micromachines, 2023 Detecting pedestrians in low-light conditions is challenging, especially in the context of wearable platforms. Infrared cameras have been employed to enhance detection capabilities, whereas low-light cameras capture the more intricate features of ...
Tianlin Li +3 more
doaj +2 more sources
YOLOv5-AC: Attention Mechanism-Based Lightweight YOLOv5 for Track Pedestrian Detection. [PDF]
Sensors (Basel), 2022 In response to the dangerous behavior of pedestrians roaming freely on unsupervised train tracks, the real-time detection of pedestrians is urgently required to ensure the safety of trains and people.
Lv H, Yan H, Liu K, Zhou Z, Jing J.
europepmc +2 more sources
Variational Pedestrian Detection [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Pedestrian detection in a crowd is a challenging task due to a high number of mutually-occluding human instances, which brings ambiguity and optimization difficulties to the current IoU-based ground truth assignment procedure in classical object detection methods.
Yuang Zhang +5 more
openaire +2 more sources
TFDet: Target-Aware Fusion for RGB-T Pedestrian Detection [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2023 Pedestrian detection plays a critical role in computer vision as it contributes to ensuring traffic safety. Existing methods that rely solely on RGB images suffer from performance degradation under low-light conditions due to the lack of useful ...
Xue Zhang +7 more
semanticscholar +1 more source