A repository for the paper "Real-Time Traffic Sign Recognition Based on Efficient CNNs in the Wild"
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Updated
Apr 6, 2020 - Jupyter Notebook
A repository for the paper "Real-Time Traffic Sign Recognition Based on Efficient CNNs in the Wild"
Deep leaning for traffic sign classification in keras and python
Code for the paper entitled "Deep neural network for traffic sign recognition systems: An analysis of spatial transformers and stochastic optimisation methods".
Classify traffic signs by three classic ConvNets architecture using GTSRB dataset.
German Traffic Sign Recognition Benchmark (GTSRB) AlexNet pycaffe model. http://benchmark.ini.rub.de/
Traffic Sign Detection 🇩🇪 Praktische Implementierung einer Verkehrszeichenerkennung mit OpenCV und Tensorflow im Rahmen einer Studienarbeit.
TensorFlow Lite classification model for German Traffic Sign Benchmarks dataset, built on top of MobileNet v1
Detect traffic sign and recognize them using Image Processing algorithms and Machine Learning(Random Forest)
GTSRB (Traffic sign), MNIST, CIFAR image classification and other good starting point
Robust Transformer with Locality Inductive Bias and Feature Normalization (JESTECH 2023)
The German Traffic Sign Benchmark is a multi-class, single-image classification challenge. Humans are capable of recognizing the large variety of existing road signs with close to 100% correctness.Then what about machines, Can we make them intelligent like humans ?
Dieses Projekt beschäftigt sich mit der Entwicklung eines flachen CNN zur Erkennung von Verkehrsschildern. Das Projekt beinhaltet alle dazu benötigten Programme und Tools.
Fast and accurate ResNet for the GTSRB dataset
Building autonomous vehicles from the ground up!
A CNN model to classify German traffic signs
Detect and Analyze Trojan attacks on deep neural networks that are designed to be difficult to detect.
Classify traffic signs by using the AlexNet and GoogLeNet architecture using GTSRB dataset and comparing the two
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