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Real-Time Object Detection

Real-Time Object Detection is a computer vision task that involves identifying and locating objects of interest in real-time video sequences with fast inference while maintaining a base level of accuracy.

This is typically solved using algorithms that combine object detection and tracking techniques to accurately detect and track objects in real-time. They use a combination of feature extraction, object proposal generation, and classification to detect and localize objects of interest.

( Image credit: CenterNet )

Papers

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Showing 101–125 of 259 papers

TitleStatusHype
A Survey on Deep Domain Adaptation and Tiny Object Detection Challenges, Techniques and Datasets—0
HGO-YOLO: Advancing Anomaly Behavior Detection with Hierarchical Features and Lightweight Optimized Detection—0
ARTOS -- Adaptive Real-Time Object Detection System—0
2D Object Detection: A Survey—0
A Comprehensive Study of Real-Time Object Detection Networks Across Multiple Domains: A Survey—0
Human-in-the-loop Reasoning For Traffic Sign Detection: Collaborative Approach Yolo With Video-llava—0
Image Models for large-scale Object Detection and Classification—0
Inception-YOLO: Computational cost and accuracy improvement of the YOLOv5 model based on employing modified CSP, SPPF, and inception modules—0
Indian Commercial Truck License Plate Detection and Recognition for Weighbridge Automation—0
Industrial object, machine part and defect recognition towards fully automated industrial monitoring employing deep learning. The case of multilevel VGG19—0
Inference of Quantized Neural Networks on Heterogeneous All-Programmable Devices—0
Leveraging the Edge and Cloud for V2X-Based Real-Time Object Detection in Autonomous Driving—0
PointCompress3D: A Point Cloud Compression Framework for Roadside LiDARs in Intelligent Transportation Systems—0
Lightweight Object Detection: A Study Based on YOLOv7 Integrated with ShuffleNetv2 and Vision Transformer—0
Globally-scalable Automated Target Recognition (GATR)—0
Liquid Leak Detection Using Thermal Images—0
GLCM-Based Feature Combination for Extraction Model Optimization in Object Detection Using Machine Learning—0
MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection—0
Generalized Haar Filter based Deep Networks for Real-Time Object Detection in Traffic Scene—0
FVNet: 3D Front-View Proposal Generation for Real-Time Object Detection from Point Clouds—0
A Deep Learning Framework for Detection of Targets in Thermal Images to Improve Firefighting—0
CorrDiff: Adaptive Delay-aware Detector with Temporal Cue Inputs for Real-time Object Detection—0
Modality-Buffet for Real-Time Object Detection—0
Artificial Intelligence Enabled Traffic Monitoring System—0
Precision and Adaptability of YOLOv5 and YOLOv8 in Dynamic Robotic Environments—0
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