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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 51–75 of 127 papers

TitleStatusHype
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
On the Natural Robustness of Vision-Language Models Against Visual Perception Attacks in Autonomous Driving—0
On the Relation between Optical Aperture and Automotive Object Detection—0
Optimized Detection and Classification on GTRSB: Advancing Traffic Sign Recognition with Convolutional Neural Networks—0
Physical Adversarial Attacks on Deep Neural Networks for Traffic Sign Recognition: A Feasibility Study—0
Prioritizing Corners in OoD Detectors via Symbolic String Manipulation—0
Real-Time Traffic Sign Detection: A Case Study in a Santa Clara Suburban Neighborhood—0
Regula Sub-rosa: Latent Backdoor Attacks on Deep Neural Networks—0
Revisiting Physical-World Adversarial Attack on Traffic Sign Recognition: A Commercial Systems Perspective—0
Revolutionizing Traffic Sign Recognition: Unveiling the Potential of Vision Transformers—0
Road images augmentation with synthetic traffic signs using neural networks—0
Road Traffic Sign Recognition method using Siamese network Combining Efficient-CNN based Encoder—0
Robustness Out of the Box: Compositional Representations Naturally Defend Against Black-Box Patch Attacks—0
Robustness testing of AI systems: A case study for traffic sign recognition—0
Sardino: Ultra-Fast Dynamic Ensemble for Secure Visual Sensing at Mobile Edge—0
Secure Traffic Sign Recognition: An Attention-Enabled Universal Image Inpainting Mechanism against Light Patch Attacks—0
Securing Traffic Sign Recognition Systems in Autonomous Vehicles—0
Security for Machine Learning-based Systems: Attacks and Challenges during Training and Inference—0
Snowball Adversarial Attack on Traffic Sign Classification—0
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
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