AI for Autonomous Vehicles
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Updated
Mar 28, 2024 - Jupyter Notebook
AI for Autonomous Vehicles
Use of Deep neural networks and convolutional neural networks to classify German traffic signs. Try this app :- https://trafficsignapp.herokuapp.com/
🚸⛔Novel Deep Convolutional Network is proposed for traffic sign classification that achieves outstanding performance on GTSRB surpassing the best human performance of 98.84%.
Speed Limit Recognition using VGG19 architecture on GTSRB dataset in Caffe
Traffic sign classifier with tensorflow
Experimental Adversarial Attack notebooks on CV models
Training a Convolutional Neural Network to perform multi-class classification on the German Traffic Sign Recognition Benchmark
Deep Learning for Autonomous Driving - Laboratory
An implementation of CS50's AI project using computer vision to determine the type of traffic signs in photos.
Dieses Projekt beschäftigt sich mit der Entwicklung eines flachen CNN zur Erkennung von Verkehrsschildern. Das Projekt beinhaltet alle dazu benötigten Programme und Tools.
A CNN model to classify German traffic signs
Image Scaling Attack on German Traffic Sign Recognition Benchmark CNN Model.
This project attempts to implement transfer learning by retraining VGG16 network to recognise traffic signs
Traffic Sign Classification (GTSRB dataset) using Random Forest Classifier
Convolutional Neural Network for classification of traffic signs
Matrix Capsules experiment on German Traffic Sign Recognition Benchmark (GTSRB)
My thesis code for Traffic Sign Recognition using 2 different datasets (GTSRB and DFG) and different kinds of models (CNN, STN, ViT).
traffic sign classification on the german traffic sign recognition benchmark dataset using CNN
Recognition of Quebec road signs using transfer learning with Python.
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