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YOLOv11 is the latest iteration in the You Only Look Once (YOLO) series of real-time object detectors, introducing novel architectural modules to improve feature extraction and small-object detection. In this paper, we present a detailed…

计算机视觉与模式识别 · 计算机科学 2026-04-07 Nikhileswara Rao Sulake

Automatic detection and classification of pavement distresses is critical in timely maintaining and rehabilitating pavement surfaces. With the evolution of deep learning and high performance computing, the feasibility of vision-based…

计算机视觉与模式识别 · 计算机科学 2020-12-01 Vishal Mandal , Abdul Rashid Mussah , Yaw Adu-Gyamfi

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

Automated pavement distresses detection using road images remains a challenging topic in the computer vision research community. Recent developments in deep learning has led to considerable research activity directed towards improving the…

计算机视觉与模式识别 · 计算机科学 2020-04-29 Hamed Majidifard , Peng Jin , Yaw Adu-Gyamfi , William G. Buttlar

The escalating risk of collisions and the accumulation of space debris in Low Earth Orbit (LEO) has reached critical concern due to the ever increasing number of spacecraft. Addressing this crisis, especially in dealing with non-cooperative…

计算机视觉与模式识别 · 计算机科学 2023-11-28 Mackenzie J. Meni , Trupti Mahendrakar , Olivia D. M. Raney , Ryan T. White , Michael L. Mayo , Kevin Pilkiewicz

Autonomous driving technology is progressively transforming traditional car driving methods, marking a significant milestone in modern transportation. Object detection serves as a cornerstone of autonomous systems, playing a vital role in…

计算机视觉与模式识别 · 计算机科学 2025-07-24 Shijie Lyu

Computer vision relies on labeled datasets for training and evaluation in detecting and recognizing objects. The popular computer vision program, YOLO ("You Only Look Once"), has been shown to accurately detect objects in many major image…

计算机视觉与模式识别 · 计算机科学 2019-01-01 Caleb Tung , Matthew R. Kelleher , Ryan J. Schlueter , Binhan Xu , Yung-Hsiang Lu , George K. Thiruvathukal , Yen-Kuang Chen , Yang Lu

This study investigates the application of single and two-stage 2D-object detection algorithms like You Only Look Once (YOLO), Real-Time DEtection TRansformer (RT-DETR) algorithm for automated object detection to enhance road safety for…

计算机视觉与模式识别 · 计算机科学 2024-12-31 Stefan Schoder

Crack is one of the most common road distresses which may pose road safety hazards. Generally, crack detection is performed by either certified inspectors or structural engineers. This task is, however, time-consuming, subjective and…

计算机视觉与模式识别 · 计算机科学 2019-04-19 Rui Fan , Mohammud Junaid Bocus , Yilong Zhu , Jianhao Jiao , Li Wang , Fulong Ma , Shanshan Cheng , Ming Liu

We present an enhanced YOLOv8 real time vehicle detection and classification framework, for estimating carbon emissions in urban environments. The system enhances YOLOv8 architecture to detect, segment, and track vehicles from live traffic…

计算机视觉与模式识别 · 计算机科学 2025-06-25 Ammar K Al Mhdawi , Nonso Nnamoko , Safanah Mudheher Raafat , M. K. S. Al-Mhdawi , Amjad J Humaidi

Object detection for street-level objects can be applied to various use cases, from car and traffic detection to the self-driving car system. Therefore, finding the best object detection algorithm is essential to apply it effectively. Many…

计算机视觉与模式识别 · 计算机科学 2022-08-25 Martinus Grady Naftali , Jason Sebastian Sulistyawan , Kelvin Julian

Pavement crack detection is a critical task for insuring road safety. Manual crack detection is extremely time-consuming. Therefore, an automatic road crack detection method is required to boost this progress. However, it remains a…

计算机视觉与模式识别 · 计算机科学 2019-01-28 Fan Yang , Lei Zhang , Sijia Yu , Danil Prokhorov , Xue Mei , Haibin Ling

The utilization of deep learning-based object detection is an effective approach to assist visually impaired individuals in avoiding obstacles. In this paper, we implemented seven different YOLO object detection models \textit{viz}.,…

计算机视觉与模式识别 · 计算机科学 2023-12-14 Chenhao He , Pramit Saha

This paper presents a comprehensive solution to address the critical challenge of liquid leaks in the oil and gas industry, leveraging advanced computer vision and deep learning methodologies. Employing You Only Look Once (YOLO) and…

计算机视觉与模式识别 · 计算机科学 2023-12-19 Kalpak Bansod , Yanshan Wan , Yugesh Rai

Traffic signs are important facilities to ensure traffic safety and smooth flow, but may be damaged due to many reasons, which poses a great safety hazard. Therefore, it is important to study a method to detect damaged traffic signs.…

计算机视觉与模式识别 · 计算机科学 2023-09-14 Tengyang Chen , Jiangtao Ren

Tunnel lining crack is a crucial indicator of tunnels' safety status. Aiming to classify and segment tunnel cracks with enhanced accuracy and efficiency, this study proposes a two-step deep learning-based method. An automatic tunnel image…

计算机视觉与模式识别 · 计算机科学 2025-07-21 Yong Feng , Xiaolei Zhang , Shijin Feng , Yong Zhao , Yihan Chen

Deep learning-based computer vision technology has grown stronger in recent years, and cross-fertilization using computer vision technology has been a popular direction in recent years. The use of computer vision technology to identify…

计算机视觉与模式识别 · 计算机科学 2023-03-21 Zhifeng Wang , Jialong Yao , Chunyan Zeng , Wanxuan Wu , Hongmin Xu , Yang Yang

Vision is a major component in several digital technologies and tools used in agriculture. The object detector, You Look Only Once (YOLO), has gained popularity in agriculture in a relatively short span due to its state-of-the-art…

计算机视觉与模式识别 · 计算机科学 2024-01-22 Chetan M Badgujar , Alwin Poulose , Hao Gan

Any intelligent traffic monitoring system must be able to detect anomalies such as traffic accidents in real time. In this paper, we propose a Decision-Tree - enabled approach powered by Deep Learning for extracting anomalies from traffic…

计算机视觉与模式识别 · 计算机科学 2021-04-15 Armstrong Aboah , Maged Shoman , Vishal Mandal , Sayedomidreza Davami , Yaw Adu-Gyamfi , Anuj Sharma