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This study presents a detailed analysis of the YOLOv8 object detection model, focusing on its architecture, training techniques, and performance improvements over previous iterations like YOLOv5. Key innovations, including the CSPNet…

计算机视觉与模式识别 · 计算机科学 2024-08-29 Muhammad Yaseen

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…

计算机视觉与模式识别 · 计算机科学 2024-10-22 Amelia Jones

Existing detection methods for insulator defect identification from unmanned aerial vehicles (UAV) struggle with complex background scenes and small objects, leading to suboptimal accuracy and a high number of false positives detection.…

计算机视觉与模式识别 · 计算机科学 2024-10-16 Olalekan Akindele , Joshua Atolagbe

The growing need for video surveillance in public spaces has created a demand for systems that can track individuals across multiple cameras feeds in real-time. While existing tracking systems have achieved impressive performance using deep…

计算机视觉与模式识别 · 计算机科学 2023-09-26 Vipin Gautam , Shitala Prasad , Sharad Sinha

Reliable helipad detection is essential for Autonomous Aerial Vehicle (AAV) landing, especially under GPS-denied or visually degraded conditions. While modern detectors such as YOLOv8 offer strong baseline performance, single-model…

机器人学 · 计算机科学 2025-12-19 Humaira Tasnim , Ashik E Rasul , Bruce Jo , Hyung-Jin Yoon

Ensuring safety on construction sites is critical, with helmets playing a key role in reducing injuries. Traditional safety checks are labor-intensive and often insufficient. This study presents a computer vision-based solution using YOLO…

计算机视觉与模式识别 · 计算机科学 2024-10-29 Xiaoyi Liu , Ruina Du , Lianghao Tan , Junran Xu , Chen Chen , Huangqi Jiang , Saleh Aldwais

Driver drowsiness remains a critical factor in road accidents, accounting for thousands of fatalities and injuries each year. This paper presents a comprehensive evaluation of real-time, non-intrusive drowsiness detection methods, focusing…

计算机视觉与模式识别 · 计算机科学 2025-09-23 Dilshara Herath , Chinthaka Abeyrathne , Prabhani Jayaweera

YOLO has become a central real-time object detection system for robotics, driverless cars, and video monitoring applications. We present a comprehensive analysis of YOLO's evolution, examining the innovations and contributions in each…

计算机视觉与模式识别 · 计算机科学 2024-02-06 Juan Terven , Diana Cordova-Esparza

This project aims to develop a system to run the object detection model under low power consumption conditions. The detection scene is set as an outdoor traveling scene, and the detection categories include people and vehicles. In this…

系统与控制 · 电气工程与系统科学 2025-07-23 Jiyue Jiang , Mingtong Chen , Zhengbao Yang

In high-risk railway construction, personal protective equipment monitoring is critical but challenging due to small and frequently obstructed targets. We propose YOLO-EA, an innovative model that enhances safety measure detection by…

计算机视觉与模式识别 · 计算机科学 2024-11-06 Hao Liu , Xue Qin

Falls represent one of the most detrimental occurrences for the elderly. Given the continually increasing ageing demographic, there is a pressing demand for advancing fall detection systems. The swift progress in sensor networks and the…

人机交互 · 计算机科学 2024-08-31 Balachandra D S , Maithreyee M S , Saipavan B M , Shashank S , P Devaki , Ms. Ashwini M

This paper presents an approach for rail line detection and the identification of human beings in proximity to the track, utilizing the YOLOv5 deep learning model to mitigate potential accidents. The technique incorporates real-time video…

计算机视觉与模式识别 · 计算机科学 2025-07-08 Mehrab Hosain , Rajiv Kapoor

Object detection is a crucial component in autonomous vehicle systems. It enables the vehicle to perceive and understand its environment by identifying and locating various objects around it. By utilizing advanced imaging and deep learning…

计算机视觉与模式识别 · 计算机科学 2026-02-03 Bsher Karbouj , Adam Michael Altenbuchner , Joerg Krueger

The You Only Look Once (YOLO) architecture is crucial for real-time object detection. However, deploying it in resource-constrained environments such as unmanned aerial vehicles (UAVs) requires efficient transfer learning. Although layer…

计算机视觉与模式识别 · 计算机科学 2025-09-09 Andrzej D. Dobrzycki , Ana M. Bernardos , José R. Casar

Autonomous vehicle perception systems require robust pedestrian detection, particularly on geometrically complex roadways like Type-S curved surfaces, where standard RGB camera-based methods face limitations. This paper introduces YOLO-APD,…

计算机视觉与模式识别 · 计算机科学 2025-07-09 Aquino Joctum , John Kandiri

Small object detection has major applications in the fields of UAVs, surveillance, farming and many others. In this work we investigate the performance of state of the art Yolo based object detection models for the task of small object…

计算机视觉与模式识别 · 计算机科学 2022-03-10 Muhammed Can Keles , Batuhan Salmanoglu , Mehmet Serdar Guzel , Baran Gursoy , Gazi Erkan Bostanci

Traditional automated toll collection systems depend on complex hardware configurations, that require huge investments in installation and maintenance. This research paper presents an innovative approach to revolutionize automated toll…

计算机视觉与模式识别 · 计算机科学 2024-12-18 Karthik Sivakoti

With the rapid development of urban underground rail vehicles,subway positioning, which plays a fundamental role in the traffic navigation and collision avoidance systems, has become a research hot-spot these years. Most current subway…

计算机视觉与模式识别 · 计算机科学 2024-10-15 Jiajie Song , Ningfang Song , Xiong Pan , Xiaoxin Liu , Can Chen , Jingchun Cheng

The increasing shortage of nursing staff and the acute risk of falls in nursing homes pose significant challenges for the healthcare system. This study presents the development of an automated fall detection system integrated into care…

For monitoring the night sky conditions, wide-angle all-sky cameras are used in most astronomical observatories to monitor the sky cloudiness. In this manuscript, we apply a deep-learning approach for automating the identification of…

天体物理仪器与方法 · 物理学 2025-03-25 Mohammad H. Zhoolideh Haghighi , Alireza Ghasrimanesh , Habib Khosroshahi