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Traffic Sign Recognition

Traffic sign recognition is the task of recognising traffic signs in an image or video.

( Image credit: Novel Deep Learning Model for Traffic Sign Detection Using Capsule Networks )

Papers

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Showing 76–100 of 127 papers

TitleStatusHype
Think Twice Before Recognizing: Large Multimodal Models for General Fine-grained Traffic Sign Recognition—0
Towards Audit Requirements for AI-based Systems in Mobility Applications—0
Towards Multimodal Multitask Scene Understanding Models for Indoor Mobile Agents—0
Traffic Sign Classification Using Deep and Quantum Neural Networks—0
Traffic Sign Recognition Using Local Vision Transformer—0
Training A Neural Network For Partially Occluded Road Sign Identification In The Context Of Autonomous Vehicles—0
Visualizing Color-wise Saliency of Black-Box Image Classification Models—0
Voice-Assisted Real-Time Traffic Sign Recognition System Using Convolutional Neural Network—0
YOLO-TS: Real-Time Traffic Sign Detection with Enhanced Accuracy Using Optimized Receptive Fields and Anchor-Free Fusion—0
NeuronInspect: Detecting Backdoors in Neural Networks via Output Explanations—0
A Deeply Supervised Semantic Segmentation Method Based on GAN—0
A Digital Twin prototype for traffic sign recognition of a learning-enabled autonomous vehicle—0
Advancing Autonomous Vehicle Intelligence: Deep Learning and Multimodal LLM for Traffic Sign Recognition and Robust Lane Detection—0
Adversarial Attacks on Traffic Sign Recognition: A Survey—0
Adversarial Robustness Through Artifact Design—0
A Hybrid Quantum-Classical AI-Based Detection Strategy for Generative Adversarial Network-Based Deepfake Attacks on an Autonomous Vehicle Traffic Sign Classification System—0
A Low-cost and Ultra-lightweight Binary Neural Network for Traffic Signal Recognition—0
An Acceleration Method Based on Deep Learning and Multilinear Feature Space—0
Analysis of Classifier Training on Synthetic Data for Cross-Domain Datasets—0
A novel pLSA based Traffic Signs Classification System—0
Why Autonomous Vehicles Are Not Ready Yet: A Multi-Disciplinary Review of Problems, Attempted Solutions, and Future Directions—0
Applying the Decisiveness and Robustness Metrics to Convolutional Neural Networks—0
AppSign: Multi-level Approximate Computing for Real-Time Traffic Sign Recognition in Autonomous Vehicles—0
Assurance Monitoring of Cyber-Physical Systems with Machine Learning Components—0
Assurance Monitoring of Learning Enabled Cyber-Physical Systems Using Inductive Conformal Prediction based on Distance Learning—0
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