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Object detection as part of computer vision can be crucial for traffic management, emergency response, autonomous vehicles, and smart cities. Despite significant advances in object detection, detecting small objects in images captured by…

计算机视觉与模式识别 · 计算机科学 2024-08-12 Boshra Khalili , Andrew W. Smyth

This research paper proposes a novel methodology for image-to-image style transfer on objects utilizing a single deep convolutional neural network. The proposed approach leverages the You Only Look Once version 8 (YOLOv8) segmentation model…

计算机视觉与模式识别 · 计算机科学 2024-04-16 Harshmohan Kulkarni , Om Khare , Ninad Barve , Sunil Mane

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

object detection framework plays crucial role in autonomous driving. In this paper, we introduce the real-time object detection framework called You Only Look Once (YOLOv1) and the related improvements of YOLOv2. We further explore the…

计算机视觉与模式识别 · 计算机科学 2019-05-14 Shouyu Wang , Weitao Tang

Coral reefs are vital ecosystems that are under increasing threat due to local human impacts and climate change. Efficient and accurate monitoring of coral reefs is crucial for their conservation and management. In this paper, we present an…

计算机视觉与模式识别 · 计算机科学 2024-05-27 Ouassine Younes , Zahir Jihad , Conruyt Noël , Kayal Mohsen , A. Martin Philippe , Chenin Eric , Bigot Lionel , Vignes Lebbe Regine

For years, the YOLO series has been the de facto industry-level standard for efficient object detection. The YOLO community has prospered overwhelmingly to enrich its use in a multitude of hardware platforms and abundant scenarios. In this…

Accurate vehicle detection is essential for the development of intelligent transportation systems, autonomous driving, and traffic monitoring. This paper presents a detailed analysis of YOLO11, the latest advancement in the YOLO series of…

计算机视觉与模式识别 · 计算机科学 2024-10-31 Mujadded Al Rabbani Alif

Helmet detection is crucial for advancing protection levels in public road traffic dynamics. This problem statement translates to an object detection task. Therefore, this paper compares recent You Only Look Once (YOLO) models in the…

计算机视觉与模式识别 · 计算机科学 2024-12-30 Vaikunth M , Dejey D , Vishaal C , Balamurali S

This paper presents a generalized model for real-time detection of flying objects that can be used for transfer learning and further research, as well as a refined model that achieves state-of-the-art results for flying object detection. We…

计算机视觉与模式识别 · 计算机科学 2024-05-24 Dillon Reis , Jordan Kupec , Jacqueline Hong , Ahmad Daoudi

Saliency-driven image and video coding for humans has gained importance in the recent past. In this paper, we propose such a saliency-driven coding framework for the video coding for machines task using the latest video coding standard…

计算机视觉与模式识别 · 计算机科学 2022-03-14 Kristian Fischer , Felix Fleckenstein , Christian Herglotz , André Kaup

Current state-of-the-art one-stage object detectors are limited by treating each image region separately without considering possible relations of the objects. This causes dependency solely on high-quality convolutional feature…

计算机视觉与模式识别 · 计算机科学 2022-03-01 Tolga Aksoy , Ugur Halici

You Only Look Once (YOLO)-based object detectors have shown remarkable accuracy for automated brain tumor detection. In this paper, we develop a novel BGF-YOLO architecture by incorporating Bi-level routing attention, Generalized feature…

计算机视觉与模式识别 · 计算机科学 2024-10-15 Ming Kang , Chee-Ming Ting , Fung Fung Ting , Raphaël C. -W. Phan

Computer vision, particularly vehicle and pedestrian identification is critical to the evolution of autonomous driving, artificial intelligence, and video surveillance. Current traffic monitoring systems confront major difficulty in…

计算机视觉与模式识别 · 计算机科学 2024-04-15 Md Nahid Sadik , Tahmim Hossain , Faisal Sayeed

This paper presents an architectural analysis of YOLOv12, a significant advancement in single-stage, real-time object detection building upon the strengths of its predecessors while introducing key improvements. The model incorporates an…

计算机视觉与模式识别 · 计算机科学 2025-02-21 Mujadded Al Rabbani Alif , Muhammad Hussain

This paper provides an extensive evaluation of YOLO object detection models (v5, v8, v9, v10, v11) by com- paring their performance across various hardware platforms and optimization libraries. Our study investigates inference speed and…

计算机视觉与模式识别 · 计算机科学 2025-04-15 Muhammad Fasih Tariq , Muhammad Azeem Javed

The integration of large-scale circuits and systems emphasizes the importance of automated defect detection of electronic components. The YOLO image detection model has been used to detect PCB defects and it has become a typical AI-assisted…

计算机视觉与模式识别 · 计算机科学 2025-07-08 Hengyi Zhu , Linye Wei , He Li

The task of locating and classifying different types of vehicles has become a vital element in numerous applications of automation and intelligent systems ranging from traffic surveillance to vehicle identification and many more. In recent…

We introduce YOLO9000, a state-of-the-art, real-time object detection system that can detect over 9000 object categories. First we propose various improvements to the YOLO detection method, both novel and drawn from prior work. The improved…

计算机视觉与模式识别 · 计算机科学 2016-12-28 Joseph Redmon , Ali Farhadi

You Look Only Once (YOLO) models have been widely used for building real-time object detectors across various domains. With the increasing frequency of new YOLO versions being released, key questions arise. Are the newer versions always…

计算机视觉与模式识别 · 计算机科学 2025-04-14 Tianyou Jiang , Yang Zhong

Forensic science plays a crucial role in legal investigations, and the use of advanced technologies, such as object detection based on machine learning methods, can enhance the efficiency and accuracy of forensic analysis. Human hands are…

计算机视觉与模式识别 · 计算机科学 2024-12-24 Thanh Thi Nguyen , Campbell Wilson , Imad Khan , Janis Dalins