Comparison of Different CNN Frameworks for image classification. TensorFlow

Classify Traffic Signs.

Convolutional Neural Networks (CNN) with Computer Vision (CV) for GTSRB Traffic Sign Classification

Notebook and model for German Traffic Sign Recognition Benchmark (GTSRB) Dataset. The notebook contains an extensive EDA for the dataset and trains a CNN classifier on the benchmark.

Detect and Analyze Trojan attacks on deep neural networks that are designed to be difficult to detect.

Traffic sign classifier trained using fastai and deployed to Android using PyTorch Mobile

A CNN model to classify German traffic signs

A web app for classifying traffic signs using a deep learning model trained on the GTSRB dataset.

Generating synthetic traffic sign datasets

Dieses Projekt beschäftigt sich mit der Entwicklung eines flachen CNN zur Erkennung von Verkehrsschildern. Das Projekt beinhaltet alle dazu benötigten Programme und Tools.

Traffic Sign Classification (GTSRB dataset) using Random Forest Classifier

A practice for using CNN to recognize road signs.

Open source neural network solutions for the GTSRB challenge

Part of my Master Thesis in Autonomous Driving.

This project aims to develop a neural network using TensorFlow to classify traffic signs from images, utilizing the German Traffic Sign Recognition Benchmark (GTSRB) dataset.

Detect traffic sign and recognize them using Image Processing algorithms and Machine Learning(Random Forest)

Fast and accurate ResNet for the GTSRB dataset

Training a VGG16 Network to Classify Traffic Signs using the German Traffic Sign Recognition Benchmark (GTSRB)

Building autonomous vehicles from the ground up!