Papers Real-Time Object Detection
“Real-Time Object Detection” 태그가 달린 논문 298편 · 필터 해제
PILAR: Personalizing Augmented Reality Interactions with LLM-based Human-Centric and Trustworthy Explanations for Daily Use Cases
Artificial intelligence (AI)-driven augmented reality (AR) systems are becoming increasingly integrated into daily life, and with this growth comes a greater need for explainability in real-time user interactions. Tradit…
Real-Time Object DetectionVajraV1 -- The most accurate Real Time Object Detector of the YOLO family
Recent years have seen significant advances in real-time object detection, with the release of YOLOv10, YOLO11, YOLOv12, and YOLOv13 between 2024 and 2025. This technical report presents the VajraV1 model architecture, w…
Real-Time Object DetectionAn AI-Powered Autonomous Underwater System for Sea Exploration and Scientific Research
Traditional sea exploration faces significant challenges due to extreme conditions, limited visibility, and high costs, resulting in vast unexplored ocean regions. This paper presents an innovative AI-powered Autonomous …
Real-Time Object DetectionDimensionality ReductionAIDEN: Design and Pilot Study of an AI Assistant for the Visually Impaired
This paper presents AIDEN, an artificial intelligence-based assistant designed to enhance the autonomy and daily quality of life of visually impaired individuals, who often struggle with object identification, text readi…
Real-Time Object DetectionYOLO-SAT: A Data-based and Model-based Enhanced YOLOv12 Model for Desert Waste Detection and Classification
The global waste crisis is escalating, with solid waste generation expected to increase tremendously in the coming years. Traditional waste collection methods, particularly in remote or harsh environments like deserts, a…
Real-Time Object DetectionData AugmentationDetecting Unauthorized Vehicles using Deep Learning for Smart Cities: A Case Study on Bangladesh
Modes of transportation vary across countries depending on geographical location and cultural context. In South Asian countries rickshaws are among the most common means of local transport. Based on their mode of operati…
Real-Time Object DetectionRT-DETRv4: Painlessly Furthering Real-Time Object Detection with Vision Foundation Models
Real-time object detection has achieved substantial progress through meticulously designed architectures and optimization strategies. However, the pursuit of high-speed inference via lightweight network designs often lea…
Real-Time Object DetectionComparative Analysis of Object Detection Algorithms for Surface Defect Detection
This article compares the performance of six prominent object detection algorithms, YOLOv11, RetinaNet, Fast R-CNN, YOLOv8, RT-DETR, and DETR, on the NEU-DET surface defect detection dataset, comprising images representi…
Real-Time Object DetectionKinematic Analysis and Integration of Vision Algorithms for a Mobile Manipulator Employed Inside a Self-Driving Laboratory
Recent advances in robotics and autonomous systems have broadened the use of robots in laboratory settings, including automated synthesis, scalable reaction workflows, and collaborative tasks in self-driving laboratories…
Real-Time Object DetectionPose EstimationEnhancing Maritime Object Detection in Real-Time with RT-DETR and Data Augmentation
Maritime object detection faces essential challenges due to the small target size and limitations of labeled real RGB data. This paper will present a real-time object detection system based on RT-DETR, enhanced by employ…
Real-Time Object DetectionData AugmentationYOLO26: Key Architectural Enhancements and Performance Benchmarking for Real-Time Object Detection
This study presents a comprehensive analysis of Ultralytics YOLO26(also called as YOLOv26), highlighting its key architectural enhancements and performance benchmarking for real-time object detection. YOLO26, released in…
Real-Time Object DetectionInstance SegmentationReal-Time Object Detection Meets DINOv3
Driven by the simple and effective Dense O2O, DEIM demonstrates faster convergence and enhanced performance. In this work, we extend it with DINOv3 features, resulting in DEIMv2. DEIMv2 spans eight model sizes from X to …
Real-Time Object DetectionAn Empirical Study on the Robustness of YOLO Models for Underwater Object Detection
Underwater object detection (UOD) remains a critical challenge in computer vision due to underwater distortions which degrade low-level features and compromise the reliability of even state-of-the-art detectors. While YO…
Real-Time Object DetectionDomain AdaptationCheck Field Detection Agent (CFD-Agent) using Multimodal Large Language and Vision Language Models
Checks remain a foundational instrument in the financial ecosystem, facilitating substantial transaction volumes across institutions. However, their continued use also renders them a persistent target for fraud, undersco…
Real-Time Object DetectionFraud DetectionAn Analysis of Layer-Freezing Strategies for Enhanced Transfer Learning in YOLO Architectures
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 learnin…
Real-Time Object DetectionTransfer LearningFederated Reinforcement Learning for Runtime Optimization of AI Applications in Smart Eyewears
Extended reality technologies are transforming fields such as healthcare, entertainment, and education, with Smart Eye-Wears (SEWs) and Artificial Intelligence (AI) playing a crucial role. However, SEWs face inherent lim…
Real-Time Object DetectionReinforcement LearningYOLOv1 to YOLOv11: A Comprehensive Survey of Real-Time Object Detection Innovations and Challenges
Over the past decade, object detection has advanced significantly, with the YOLO (You Only Look Once) family of models transforming the landscape of real-time vision applications through unified, end-to-end detection fra…
Real-Time Object DetectionInstance SegmentationPose EstimationObject TrackingReal-Time Object Detection and Classification using YOLO for Edge FPGAs
Object detection and classification are crucial tasks across various application domains, particularly in the development of safe and reliable Advanced Driver Assistance Systems (ADAS). Existing deep learning-based metho…
Real-Time Object DetectionShrinkBox: Backdoor Attack on Object Detection to Disrupt Collision Avoidance in Machine Learning-based Advanced Driver Assistance Systems
Advanced Driver Assistance Systems (ADAS) significantly enhance road safety by detecting potential collisions and alerting drivers. However, their reliance on expensive sensor technologies such as LiDAR and radar limits …
Real-Time Object DetectionCollision AvoidanceDetection of Rail Line Track and Human Beings Near the Track to Avoid Accidents
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 incorporat…
Line Detectionobject-detectionObject DetectionReal-Time Object Detection