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Detecting pedestrians, especially under heavy occlusions, is a challenging computer vision problem with numerous real-world applications. This paper introduces a novel approach, termed as PSC-Net, for occluded pedestrian detection. The…

Computer Vision and Pattern Recognition · Computer Science 2020-03-11 Jin Xie , Yanwei Pang , Hisham Cholakkal , Rao Muhammad Anwer , Fahad Shahbaz Khan , Ling Shao

As a natural disaster with high suddenness and great destructiveness, fire has long posed a major threat to human society and ecological environment. In recent years, with the rapid development of smart city and Internet of Things (IoT)…

Computer Vision and Pattern Recognition · Computer Science 2024-09-20 Weichao Pan , Xu Wang , Wenqing Huan

We present a new version of YOLO with better performance and extended with instance segmentation called Poly-YOLO. Poly-YOLO builds on the original ideas of YOLOv3 and removes two of its weaknesses: a large amount of rewritten labels and…

Computer Vision and Pattern Recognition · Computer Science 2020-06-01 Petr Hurtik , Vojtech Molek , Jan Hula , Marek Vajgl , Pavel Vlasanek , Tomas Nejezchleba

Clustering is an unsupervised machine learning method grouping data samples into clusters of similar objects. In practice, clustering has been used in numerous applications such as banking customers profiling, document retrieval, image…

Computer Vision and Pattern Recognition · Computer Science 2021-07-06 Raphaël Couturier , Hassan N. Noura , Ola Salman , Abderrahmane Sider

This paper presents a robust approach for object detection in aerial imagery using the YOLOv5 model. We focus on identifying critical objects such as ambulances, car crashes, police vehicles, tow trucks, fire engines, overturned cars, and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Sindhu Boddu , Arindam Mukherjee

This paper presents the development of an industrial fall detection system utilizing YOLOv8 variants, enhanced by our proposed augmentation pipeline to increase dataset variance and improve detection accuracy. Among the models evaluated,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Gracile Astlin Pereira

With the rapid advancement of autonomous driving technology, efficient and accurate object detection capabilities have become crucial factors in ensuring the safety and reliability of autonomous driving systems. However, in low-visibility…

Computer Vision and Pattern Recognition · Computer Science 2024-10-24 Xiguang Li , Jiafu Chen , Yunhe Sun , Na Lin , Ammar Hawbani , Liang Zhao

YOLO is a deep neural network (DNN) model presented for robust real-time object detection following the one-stage inference approach. It outperforms other real-time object detectors in terms of speed and accuracy by a wide margin.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Mohammadamin Baghbanbashi , Mohsen Raji , Behnam Ghavami

Surface defects on Printed Circuit Boards (PCBs) directly compromise product reliability and safety. However, achieving high-precision detection is challenging because PCB defects are typically characterized by tiny sizes, high texture…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 Meng Han

Pedestrian Detection is the most critical module of an Autonomous Driving system. Although a camera is commonly used for this purpose, its quality degrades severely in low-light night time driving scenarios. On the other hand, the quality…

Computer Vision and Pattern Recognition · Computer Science 2022-01-25 Kinjal Dasgupta , Arindam Das , Sudip Das , Ujjwal Bhattacharya , Senthil Yogamani

The increasing urbanization and the growing number of vehicles in cities have underscored the need for efficient parking management systems. Traditional smart parking solutions often rely on sensors or cameras for occupancy detection, each…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Gustavo P. C. P. da Luz , Gabriel Massuyoshi Sato , Luis Fernando Gomez Gonzalez , Juliana Freitag Borin

In the current worldwide situation, pedestrian detection has reemerged as a pivotal tool for intelligent video-based systems aiming to solve tasks such as pedestrian tracking, social distancing monitoring or pedestrian mass counting.…

Computer Vision and Pattern Recognition · Computer Science 2022-04-08 Alejandro López-Cifuentes , Marcos Escudero-Viñolo , Jesús Bescós , Pablo Carballeira

Complete blood cell detection holds significant value in clinical diagnostics. Conventional manual microscopy methods suffer from time inefficiency and diagnostic inaccuracies. Existing automated detection approaches remain constrained by…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Guohua Wu , Shengqi Chen , Pengchao Deng , Wenting Yu

This paper presents a practical and lightweight solution for enhancing child detection in low-quality surveillance footage, a critical component in real-world missing child alert and daycare monitoring systems. Building upon the efficient…

Computer Vision and Pattern Recognition · Computer Science 2026-02-13 Khanh Linh Tran , Minh Nguyen Dang , Thien Nguyen Trong , Hung Nguyen Quoc , Linh Nguyen Kieu

Smart home device detection is a critical aspect of human-computer interaction. However, detecting targets in indoor environments can be challenging due to interference from ambient light and background noise. In this paper, we present a…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Jiafeng Zhang , Xuejing Pu

Multispectral pedestrian detection is attractive for around-the-clock applications due to the complementary information between RGB and thermal modalities. However, current models often fail to detect pedestrians in certain cases (e.g.,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Taeheon Kim , Sangyun Chung , Damin Yeom , Youngjoon Yu , Hak Gu Kim , Yong Man Ro

Intelligent vehicles of the future must be capable of understanding and navigating safely through their surroundings. Camera-based vehicle systems can use keypoints as well as objects as low- and high-level landmarks for GNSS-independent…

Computer Vision and Pattern Recognition · Computer Science 2024-02-07 Anton Backhaus , Thorsten Luettel , Hans-Joachim Wuensche

This research delves into the development of a fatigue detection system based on modern object detection algorithms, particularly YOLO (You Only Look Once) models, including YOLOv5, YOLOv6, YOLOv7, and YOLOv8. By comparing the performance…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Amelia Jones

Head detection provides distribution information of pedestrian, which is crucial for scene statistical analysis, traffic management, and risk assessment and early warning. However, scene complexity and large-scale variation in the real…

Computer Vision and Pattern Recognition · Computer Science 2023-10-17 Jiezhou Chen , Guankun Wang , Weixiang Liu , Xiaopin Zhong , Yibin Tian , ZongZe Wu

Recent advances in computer vision has led to a growth of interest in deploying visual analytics model on mobile devices. However, most mobile devices have limited computing power, which prohibits them from running large scale visual…

Image and Video Processing · Electrical Eng. & Systems 2022-04-18 Zhongzheng Yuan , Samyak Rawlekar , Siddharth Garg , Elza Erkip , Yao Wang