AI for Autonomous Vehicles
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Updated
Mar 28, 2024 - Jupyter Notebook
AI for Autonomous Vehicles
Introduction to CNNs in TensorFlow
Use of Deep neural networks and convolutional neural networks to classify German traffic signs. Try this app :- https://trafficsignapp.herokuapp.com/
Recognition of Quebec road signs using transfer learning with Python.
Speed Limit Recognition using VGG19 architecture on GTSRB dataset in Caffe
Traffic sign classifier with tensorflow
Experimental Adversarial Attack notebooks on CV models
Tensorflow2, working on Mnist and GTSRB
A traffic sign classifier using LeNet for Self driving cars
This code implements a CNN using TensorFlow for German traffic sign classification with the GTSRB dataset. It preprocesses data, builds the model, trains it, evaluates accuracy, and generates a confusion matrix for performance analysis.
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
This code implements a deep neural network (DNN) model for image classification using the German Traffic Sign Recognition Benchmark (GTSRB) dataset. The goal is to accurately classify traffic sign images into their respective categories.
A neural network for image classification trained/tested on the GTSRB dataset.
Custom CNN for GTSRB traffic sign detection
Training a Convolutional Neural Network to perform multi-class classification on the German Traffic Sign Recognition Benchmark
Training a VGG16 Network to Classify Traffic Signs using the German Traffic Sign Recognition Benchmark (GTSRB)
Matrix Capsules experiment on German Traffic Sign Recognition Benchmark (GTSRB)
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