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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
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
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision—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
Human-in-the-loop Reasoning For Traffic Sign Detection: Collaborative Approach Yolo With Video-llava—0
Hybrid Classical-Quantum Deep Learning Models for Autonomous Vehicle Traffic Image Classification Under Adversarial Attack—0
Improving Prediction Confidence in Learning-Enabled Autonomous Systems—0
Improving Road Signs Detection performance by Combining the Features of Hough Transform and Texture—0
Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions—0
Invisible Optical Adversarial Stripes on Traffic Sign against Autonomous Vehicles—0
Invisible Reflections: Leveraging Infrared Laser Reflections to Target Traffic Sign Perception—0
TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks—0
ITPatch: An Invisible and Triggered Physical Adversarial Patch against Traffic Sign Recognition—0
LaserGuider: A Laser Based Physical Backdoor Attack against Deep Neural Networks—0
Localized Traffic Sign Detection with Multi-scale Deconvolution Networks—0
M3E-Yolo: A New Lightweight Network for Traffic Sign Recognition—0
Mitigation of Camouflaged Adversarial Attacks in Autonomous Vehicles--A Case Study Using CARLA Simulator—0
Multi-layer Pruning Framework for Compressing Single Shot MultiBox Detector—0
Timeseries-aware Uncertainty Wrappers for Uncertainty Quantification of Information-Fusion-Enhanced AI Models based on Machine Learning—0
NTD: Non-Transferability Enabled Backdoor Detection—0
MISA: Online Defense of Trojaned Models using Misattributions—0
Gotta Catch 'Em All: Using Honeypots to Catch Adversarial Attacks on Neural NetworksCode0
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