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
Real and Pseudo Pedestrian Detection Method with CA-YOLOv5s Based on Stereo Image Fusion [PDF]
Entropy, 2022 With the development of convolutional neural networks, the effect of pedestrian detection has been greatly improved by deep learning models. However, the presence of pseudo pedestrians will lead to accuracy reduction in pedestrian detection. To solve the
Xiaowei Song +5 more
doaj +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
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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
Occlusion Handling and Multi-Scale Pedestrian Detection Based on Deep Learning: A Review
IEEE Access, 2022 Pedestrian detection is an important branch of computer vision, and has important applications in the fields of autonomous driving, artificial intelligence and video surveillance.
Fang Li, Xueyuan Li, Qi Liu, Zirui Li
doaj +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
VLPD: Context-Aware Pedestrian Detection via Vision-Language Semantic Self-Supervision [PDF]
Computer Vision and Pattern Recognition, 2023 Detecting pedestrians accurately in urban scenes is significant for realistic applications like autonomous driving or video surveillance. However, confusing human-like objects often lead to wrong detections, and small scale or heavily occluded ...
Mengyin Liu +3 more
semanticscholar +1 more source
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 +1 more source
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 +1 more source
Cross-Modality Proposal-Guided Feature Mining for Unregistered RGB-Thermal Pedestrian Detection [PDF]
IEEE transactions on multimedia, 2023 RGB-Thermal (RGB-T) pedestrian detection aims to locate pedestrians in RGB-T image pairs to exploit the complementation between the two modalities for improving detection robustness in extreme conditions.
Chao Tian +4 more
semanticscholar +1 more source