wolfapple / traffic-sign-recognitionLinks
Built and trained a deep neural network to classify traffic signs, using PyTorch. The highlights of this solution would be data preprocessing, trained with heavily augmented data and using Spatial Transformer Network.
☆37Updated 5 years ago
Alternatives and similar repositories for traffic-sign-recognition
Users that are interested in traffic-sign-recognition are comparing it to the libraries listed below
Sorting:
- Convolutional Neural Network for German Traffic Sign Recognition Benchmark☆124Updated 3 years ago
- PyTorch implementation of Kaggle GTSRB challenge with 99.8% accuracy☆57Updated 6 years ago
- LISA Traffic Signs Dataset for Pytorch. For Classification. 32x32 images. I use this to reproduce the Activation Clustering Results.☆21Updated 4 years ago
- The code of our paper: 'Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples', in Tensorflow.☆51Updated 6 months ago
- Code for the 'DARTS: Deceiving Autonomous Cars with Toxic Signs' paper☆38Updated 7 years ago
- A collection of labeled car driving datasets☆114Updated 4 years ago
- Attacking Vision based Perception in End-to-end Autonomous Driving Models☆33Updated 3 years ago
- Public release of code for Robust Physical-World Attacks on Deep Learning Visual Classification (Eykholt et al., CVPR 2018)☆111Updated 4 years ago
- Physical adversarial attack for fooling the Faster R-CNN object detector☆167Updated 5 years ago
- Classification, Object Detection, Adversarial Attack of Chinese Traffic Signs // 中式交通标志图片的分类、目标检测、对抗性攻击☆10Updated 5 years ago
- Artifacts for SLAP: Improving Physical Adversarial Examples with Short-Lived Adversarial Perturbations☆27Updated 4 years ago
- Estimating distance to objects in the scene using detection information☆171Updated 3 years ago
- Implementation of the paper "An Analysis of Adversarial Attacks and Defenses on Autonomous Driving Models"☆17Updated 5 years ago
- Track hijacking attack against Multiple-Object Tracking☆45Updated 6 years ago
- Image classification using pytorch on German Traffic Sign data set☆10Updated 4 years ago
- Deep Federated Learning for Autonomous Driving (IV'22)☆38Updated last year
- This is a reimplementation of the blog post "Building Autoencoders in Keras". Instead of using MNIST, this project uses CIFAR10.☆74Updated 6 years ago
- Generate adversarial patches against YOLOv5 🚀☆66Updated last month
- Simple pytorch implementation of FGSM and I-FGSM☆290Updated 7 years ago
- This repository contains the implementation of three adversarial example attack methods FGSM, IFGSM, MI-FGSM and one Distillation as defe…☆136Updated 4 years ago
- Traffic Sign Detection. Code for the paper entitled "Evaluation of deep neural networks for traffic sign detection systems".☆334Updated 3 years ago
- Implementation of Nvidia's DAVE2 NN in Keras, with some enhancements☆25Updated 8 years ago
- Image Classification with `sklearn.svm`☆58Updated 4 years ago
- An PyTorch implementation AlexNet.Simple, easy to use and efficient☆95Updated 2 years ago
- This library augments road images to introduce various real world scenarios that pose challenges for training neural networks of Autonomo…☆641Updated 3 years ago
- PyTorch Implementation of Adversarial Training for Free!☆248Updated 4 years ago
- A Implementation of IJCAI-19(Transferable Adversarial Attacks for Image and Video Object Detection)☆89Updated 6 years ago
- a Pytorch implementation of the paper "Generating Adversarial Examples with Adversarial Networks" (advGAN).☆275Updated 4 years ago
- "BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression Tasks"☆11Updated last year
- Real-time object detection is one of the key applications of deep neural networks (DNNs) for real-world mission-critical systems. While D…☆134Updated 2 years ago