This project aims to train a PyTorch model to detect and identify traffic signs. The images used come from the GTRSB (German Traffic Sign Recognition Benchmark) dataset, available on …

PyTorch Traffic Sign Classification: A robust CNN model for accurate traffic sign recognition. This project includes a custom-built CNN using PyTorch, data augmentation techniques for …

German Traffic Sign Detection Benchmark (GTSDB) dataset is trained on Faster R-CNN for object detection. - sidthoviti/Traffic-Sign-Detection-with-Faster-R-CNN-using-PyTorch

Apr 4, 2022 · Learn how to train a custom object detection model for traffic sign detection using PyTorch and Faster RCNN model.

Mar 27, 2019 · This is my attempt to tackle traffic signs classification problem with a deep neural network implemented in PyTorch (reaching 99.33% accuracy). The highlights of this solution …

Sep 9, 2017 · In this project, a traffic sign recognition system, divided into two parts, is presented. The first part is based on classical image processing techniques, for traffic signs extraction out …

Traffic-Signs Recognition and Classification. In this part, I trained a neural network to detect and classify different traffic signs using PyTorch, YOLOv3 and OpenCV.

Dec 10, 2020 · Traffic Sign Detection on GTSDB dataset by implementing Faster R-CNN using PyTorch. Explores object detection and finetuning.

This project presents a deep learning architecture that can identify traffic signs with close to 98% accuracy on the test set. We start from building a simple CNN model, and later on apply …

A deep-learning traffic sign detection and recognition project, using convolutional neural networks and vision transformers, with PyTorch and OpenCV over the GTSRB - German Traffic Sign. …