Implementation of Single Shot MultiBox Detector in TensorFlow, to detect and classify traffic signs
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Updated
Nov 2, 2021 - Python
Implementation of Single Shot MultiBox Detector in TensorFlow, to detect and classify traffic signs
Traffic signs detection and classification in real time
[DEPRECATED] Traffic sign detector and classifier that uses dlib and its implementation of the Felzenszwalb's version of the Histogram of Oriented Gradients (HoG) detector
Türkiye Trafik İşaretleri Veriseti - Turkish Traffic Sign Dataset
Deep leaning for traffic sign classification in keras and python
Autonomous Driving Simulator for the Portuguese Robotics Open
Traffic sign classification for the German Traffic Sign Dataset
Tie - Font Conversion of The Finnish Traffic Sign Typeface
Training a Faster R-CNN from scratch on LISA Traffic Signs dataset using TensorFlow Object Detection API
German Traffic Sign Recognition Benchmark (GTSRB) AlexNet pycaffe model. http://benchmark.ini.rub.de/
Synthetic traffic sign detectron
In this project, deep neural networks and convolutional neural networks are used to classify traffic signs. A model is trained so it can decode traffic signs from natural images by using the German Traffic Sign Dataset. After the model is trained, the model is tested on new images of traffic signs that are found on the web
Detection and recognition of traffic signs.
Developed for the TEKNOFEST Robotaxi Autonomous Vehicle Competition, an intelligent autonomous vehicle simulation featuring advanced computer vision, YOLOv4 traffic sign detection, lane following, and parking algorithms built in Webots.
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Udacity Self Driving Car Nanodegree - Traffic Sign Classifier
The German Traffic Sign Benchmark is a multi-class, single-image classification challenge. Humans are capable of recognizing the large variety of existing road signs with close to 100% correctness.Then what about machines, Can we make them intelligent like humans ?
This project recognises the traffic sign based on training data.
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