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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 1–50 of 127 papers

TitleStatusHype
CausalDiff: Causality-Inspired Disentanglement via Diffusion Model for Adversarial DefenseCode1
Benchmarking Local Robustness of High-Accuracy Binary Neural Networks for Enhanced Traffic Sign RecognitionCode1
Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous drivingCode1
Robust Transformer with Locality Inductive Bias and Feature NormalizationCode1
Simultaneously Optimizing Perturbations and Positions for Black-box Adversarial Patch AttacksCode1
GLARE: A Dataset for Traffic Sign Detection in Sun GlareCode1
Keep your Distance: Determining Sampling and Distance Thresholds in Machine Learning MonitoringCode1
Shadows can be Dangerous: Stealthy and Effective Physical-world Adversarial Attack by Natural PhenomenonCode1
A real-time and high-precision method for small traffic-signs recognitionCode1
Toward Improving Confidence in Autonomous Vehicle Software: A Study on Traffic Sign Recognition SystemsCode1
Adversarial Sticker: A Stealthy Attack Method in the Physical WorldCode1
Sill-Net: Feature Augmentation with Separated Illumination RepresentationCode1
SLAP: Improving Physical Adversarial Examples with Short-Lived Adversarial PerturbationsCode1
Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent AlignmentCode1
Finding Optimal Kernel Size and Dimension in Convolutional Neural Networks An Architecture Optimization Approach—0
On the Natural Robustness of Vision-Language Models Against Visual Perception Attacks in Autonomous Driving—0
Securing Traffic Sign Recognition Systems in Autonomous Vehicles—0
FIGhost: Fluorescent Ink-based Stealthy and Flexible Backdoor Attacks on Physical Traffic Sign Recognition—0
Enhancing Traffic Sign Recognition On The Performance Based On Yolov8—0
Training A Neural Network For Partially Occluded Road Sign Identification In The Context Of Autonomous Vehicles—0
Advancing Autonomous Vehicle Intelligence: Deep Learning and Multimodal LLM for Traffic Sign Recognition and Robust Lane Detection—0
Snowball Adversarial Attack on Traffic Sign Classification—0
Road Traffic Sign Recognition method using Siamese network Combining Efficient-CNN based Encoder—0
Mitigation of Camouflaged Adversarial Attacks in Autonomous Vehicles--A Case Study Using CARLA Simulator—0
On the Relation between Optical Aperture and Automotive Object Detection—0
A Low-cost and Ultra-lightweight Binary Neural Network for Traffic Signal Recognition—0
Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions—0
Evaluating Adversarial Attacks on Traffic Sign Classifiers beyond Standard BaselinesCode0
LaserGuider: A Laser Based Physical Backdoor Attack against Deep Neural Networks—0
AppSign: Multi-level Approximate Computing for Real-Time Traffic Sign Recognition in Autonomous Vehicles—0
Driving by the Rules: A Benchmark for Integrating Traffic Sign Regulations into Vectorized HD Map—0
Analysis of Classifier Training on Synthetic Data for Cross-Domain Datasets—0
YOLO-TS: Real-Time Traffic Sign Detection with Enhanced Accuracy Using Optimized Receptive Fields and Anchor-Free Fusion—0
Human-in-the-loop Reasoning For Traffic Sign Detection: Collaborative Approach Yolo With Video-llava—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
FUSED-Net: Detecting Traffic Signs with Limited Data—0
TSCLIP: Robust CLIP Fine-Tuning for Worldwide Cross-Regional Traffic Sign RecognitionCode0
SeqNet: Sequential Networks for One-Shot Traffic Sign Recognition With Transfer LearningCode0
ITPatch: An Invisible and Triggered Physical Adversarial Patch against Traffic Sign Recognition—0
Revisiting Physical-World Adversarial Attack on Traffic Sign Recognition: A Commercial Systems Perspective—0
Secure Traffic Sign Recognition: An Attention-Enabled Universal Image Inpainting Mechanism against Light Patch Attacks—0
Think Twice Before Recognizing: Large Multimodal Models for General Fine-grained Traffic Sign Recognition—0
Invisible Optical Adversarial Stripes on Traffic Sign against Autonomous Vehicles—0
Cross-domain Few-shot In-context Learning for Enhancing Traffic Sign Recognition—0
Enhancing Traffic Sign Recognition with Tailored Data Augmentation: Addressing Class Imbalance and Instance Scarcity—0
Revolutionizing Traffic Sign Recognition: Unveiling the Potential of Vision Transformers—0
Voice-Assisted Real-Time Traffic Sign Recognition System Using Convolutional Neural Network—0
Optimized Detection and Classification on GTRSB: Advancing Traffic Sign Recognition with Convolutional Neural Networks—0
A Digital Twin prototype for traffic sign recognition of a learning-enabled autonomous vehicle—0
Adversarial Robustness Through Artifact Design—0
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