Papers Real-Time Object Detection
“Real-Time Object Detection” 태그가 달린 논문 298편 · 필터 해제
Spatial-Semantic Reasoning using Large Language Models for Efficient UAV Search Operations
We present a real-time semantic navigation framework for Unmanned Aerial Vehicles (UAVs) focused on improving time efficiency in the Object Goal Navigation (ObjectNav) task. Central to our approach is a Large Language Mo…
Real-Time Object DetectionTrajectory PlanningSPK: Eliciting Structured Prior Knowledge for Interpretable Out-of-Distribution Detection in Real-Time Object Detection
Object detectors often produce over-confident predictions for objects outside their training categories, leading to so-called out-of-distribution (OoD) hallucinations. Existing approaches for detecting or mitigating such…
Out-of-Distribution DetectionReal-Time Object DetectionYOLOv14: Adaptive Real-Time Object Detection for Diverse Imaging Conditions
Real-time object detectors achieve remarkable accuracy under controlled conditions, yet degrade sharply on non-ideal inputs-fisheye distortion, game-rendered content, aerial views, and 360°panoramas. We present YOLOv14, …
Unsupervised Domain AdaptationReal-Time Object DetectionReal-Time Threat Detection from Surveillance Cameras using Machine Learning
Ensuring public safety in densely populated urban environments remains a critical challenge, necessitating the deployment of intelligent and automated video surveillance systems. Traditional surveillance approaches rely …
Real-Time Object DetectionOn-Device Generative AI for GDPR-Compliant Visual Monitoring: Natural Language Alerts from Local Object Detection
Visual monitoring systems that rely on cloud-based AI inference expose raw image data to external services, creating fundamental tensions with the data-minimisation principle of the General Data Protection Regulation (GD…
Real-Time Object DetectionYOLO26 vs. YOLOv8: A Comprehensive Architectural Benchmark of Next-Generation Real-Time Object Detection Models
This paper presents a rigorous empirical evaluation of Ultralytics YOLO26 against the YOLOv8 baseline, offering an independent real-world stress test of NMS-free architectures on non-COCO distributions. Engineered for ed…
Real-Time Object DetectionDual-Integrated Low-Latency Single-Lens Infrared Computational Imaging for Object Detection
Computational imaging enables compact infrared systems, but deep-learning pipelines that combine image reconstruction and object detection often introduce substantial inference latency. Most existing acceleration strateg…
Real-Time Object DetectionImage ReconstructionCARMEN: CORDIC-Accelerated Resource-Efficient Multi-Precision Inference Engine for Deep Learning
This paper presents CARMEN, a runtime-adaptive, CORDIC-accelerated multi-precision vector engine for resource-efficient deep learning inference. The key insight is that CORDIC iteration depth directly governs computation…
Real-Time Object DetectionFUN: A Focal U-Net Combining Reconstruction and Object Detection for Snapshot Spectral Imaging
Conventional push-broom hyperspectral imaging suffers from slow acquisition speeds, precluding real-time object detection; in contrast, snapshot spectral imaging enables instantaneous hyperspectral images (HSIs) capture,…
Real-Time Object DetectionMulti-Task LearningReal-Time Frame- and Event-based Object Detection with Spiking Neural Networks on Edge Neuromorphic Hardware: Design, Deployment and Benchmark
Real-time object detection on energy-constrained platforms is critical for applications such as UAV-based inspection, autonomous navigation, and mobile robotics. Spiking neural networks (SNNs) on neuromorphic hardware ar…
Real-Time Object DetectionDepth-Aware Rover: A Study of Edge AI and Monocular Vision for Real-World Implementation
This study analyses simulated and real-world implementations of depth-aware rover navigation, highlighting the transition from stereo vision to monocular depth estimation using edge AI. A Unity-based lunar terrain simula…
Monocular Depth EstimationReal-Time Object DetectionGLANCE: Gaze-Led Attention Network for Compressed Edge-inference
Real-time object detection in AR/VR systems faces critical computational constraints, requiring sub-10\,ms latency within tight power budgets. Inspired by biological foveal vision, we propose a two-stage pipeline that co…
Real-Time Object DetectionGaze EstimationTornadoNet: Real-Time Building Damage Detection with Ordinal Supervision
We present TornadoNet, a comprehensive benchmark for automated street-level building damage assessment evaluating how modern real-time object detection architectures and ordinal-aware supervision strategies perform under…
Building Damage AssessmentReal-Time Object DetectionOrdinal ClassificationDon't let the information slip away
Real-time object detection has advanced rapidly in recent years. The YOLO series of detectors is among the most well-known CNN-based object detection models and cannot be overlooked. The latest version, YOLOv26, was rece…
Real-Time Object DetectionLe-DETR: Revisiting Real-Time Detection Transformer with Efficient Encoder Design
Real-time object detection is crucial for real-world applications as it requires high accuracy with low latency. While Detection Transformers (DETR) have demonstrated significant performance improvements, current real-ti…
Real-Time Object DetectionA Study on Real-time Object Detection using Deep Learning
Object detection has compelling applications over a range of domains, including human-computer interfaces, security and video surveillance, navigation and road traffic monitoring, transportation systems, industrial autom…
Real-Time Object DetectionObject RecognitionDecision MakingBlocksecRT-DETR: Decentralized Privacy-Preserving and Token-Efficient Federated Transformer Learning for Secure Real-Time Object Detection in ITS
Federated real-time object detection using transformers in Intelligent Transportation Systems (ITS) faces three major challenges: (1) missing-class non-IID data heterogeneity from geographically diverse traffic environme…
Real-Time Object DetectionYOLO26: An Analysis of NMS-Free End to End Framework for Real-Time Object Detection
The ``You Only Look Once'' (YOLO) framework has long served as a standard for real-time object detection, though traditional iterations have utilized Non-Maximum Suppression (NMS) post-processing, which introduces specif…
Real-Time Object DetectionRepresentation LearningAn AI-IoT Based Smart Wheelchair with Gesture-Controlled Mobility, Deep Learning-Based Obstacle Detection, Multi-Sensor Health Monitoring, and Emergency Alert System
The growing number of differently-abled and elderly individuals demands affordable, intelligent wheelchairs that combine safe navigation with health monitoring. Traditional wheelchairs lack dynamic features, and many sma…
Real-Time Object DetectionCollision AvoidanceYOLO-Master: MOE-Accelerated with Specialized Transformers for Enhanced Real-time Detection
Existing Real-Time Object Detection (RTOD) methods commonly adopt YOLO-like architectures for their favorable trade-off between accuracy and speed. However, these models rely on static dense computation that applies unif…
Real-Time Object Detection