Traffic Sign Detection
14 papers with code • 3 benchmarks • 5 datasets
Latest papers with no code
Optimized Detection and Classification on GTRSB: Advancing Traffic Sign Recognition with Convolutional Neural Networks
In the rapidly evolving landscape of transportation, the proliferation of automobiles has made road traffic more complex, necessitating advanced vision-assisted technologies for enhanced safety and navigation.
Efficient Vision Transformer for Accurate Traffic Sign Detection
This research paper addresses the challenges associated with traffic sign detection in self-driving vehicles and driver assistance systems.
Real-Time Traffic Sign Detection: A Case Study in a Santa Clara Suburban Neighborhood
The project's primary objectives are to train the YOLOv5 model on a diverse dataset of traffic sign images and deploy the model on a suitable hardware platform capable of real-time inference.
Explainable and Trustworthy Traffic Sign Detection for Safe Autonomous Driving: An Inductive Logic Programming Approach
This approach is more robust against adversarial attacks, as it mimics human-like perception and is less susceptible to the limitations of current DNN classifiers.
Adversarial Attacks on Traffic Sign Recognition: A Survey
In this work, we survey existing works performing either digital or real-world attacks on traffic sign detection and classification models.
Context-Aware Block Net for Small Object Detection
State-of-the-art object detectors usually progressively downsample the input image until it is represented by small feature maps, which loses the spatial information and compromises the representation of small objects.
M3E-Yolo: A New Lightweight Network for Traffic Sign Recognition
Traffic sign recognition is committed to ensuring the safety of automatic driving.
Salient Sign Detection In Safe Autonomous Driving: AI Which Reasons Over Full Visual Context
Next, we use a custom salience loss function, Salience-Sensitive Focal Loss, to train a Deformable DETR object detection model in order to emphasize stronger performance on salient signs.
Traffic sign detection and recognition using event camera image reconstruction
This paper presents a method for detection and recognition of traffic signs based on information extracted from an event camera.
Traffic Sign Detection With Event Cameras and DCNN
The use of a fusion of the considered representations allows us to obtain a detector with higher accuracy of 89. 9% mAP@0. 5.