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Traffic Sign Recognition
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Traffic sign recognition is the task of recognising traffic signs in an image or video.
<span style="color:grey; opacity: 0.6">( Image credit: Novel Deep Learning Model for Traffic Sign Detection Using Capsule Networks )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Invisible Reflections: Leveraging Infrared Laser Reflections to Target Traffic Sign Perception
Why Autonomous Vehicles Are Not Ready Yet: A Multi-Disciplinary Review of Problems, Attempted Solutions, and Future Directions
Traffic Sign Recognition Using Local Vision Transformer
Efficient Vision Transformer for Accurate Traffic Sign Detection
Real-Time Traffic Sign Detection: A Case Study in a Santa Clara Suburban Neighborhood
A Deeply Supervised Semantic Segmentation Method Based on GAN
Watch Out! Simple Horizontal Class Backdoor Can Trivially Evade Defense
Benchmarking Local Robustness of High-Accuracy Binary Neural Networks for Enhanced Traffic Sign Recognition
Adversarial Attacks on Traffic Sign Recognition: A Survey
Adversarial Robustness Certification for Bayesian Neural Networks
Timeseries-aware Uncertainty Wrappers for Uncertainty Quantification of Information-Fusion-Enhanced AI Models based on Machine Learning
Effects of Real-Life Traffic Sign Alteration on YOLOv7- an Object Recognition Model
Zenseact Open Dataset: A large-scale and diverse multimodal dataset for autonomous driving
Evil from Within: Machine Learning Backdoors through Hardware Trojans
Traffic Sign Recognition Dataset and Data Augmentation
Architecturing Binarized Neural Networks for Traffic Sign Recognition
Towards Audit Requirements for AI-based Systems in Mobility Applications
Physical Adversarial Attacks on Deep Neural Networks for Traffic Sign Recognition: A Feasibility Study
Robust Transformer with Locality Inductive Bias and Feature Normalization
M3E-Yolo: A New Lightweight Network for Traffic Sign Recognition
Simultaneously Optimizing Perturbations and Positions for Black-box Adversarial Patch Attacks
Traffic Sign Classification Using Deep and Quantum Neural Networks
Towards Multimodal Multitask Scene Understanding Models for Indoor Mobile Agents
GLARE: A Dataset for Traffic Sign Detection in Sun Glare
Keep your Distance: Determining Sampling and Distance Thresholds in Machine Learning Monitoring
Efficient Federated Learning with Spike Neural Networks for Traffic Sign Recognition
Prioritizing Corners in OoD Detectors via Symbolic String Manipulation
Sardino: Ultra-Fast Dynamic Ensemble for Secure Visual Sensing at Mobile Edge
Shadows can be Dangerous: Stealthy and Effective Physical-world Adversarial Attack by Natural Phenomenon
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial Examples Against Traffic Sign Recognition Systems
Improving traffic sign recognition by active search
NTD: Non-Transferability Enabled Backdoor Detection
An Acceleration Method Based on Deep Learning and Multilinear Feature Space
Assurance Monitoring of Learning Enabled Cyber-Physical Systems Using Inductive Conformal Prediction based on Distance Learning
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