Comparison of Different CNN Frameworks for image classification. TensorFlow
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Updated
Dec 8, 2022 - Jupyter Notebook
Comparison of Different CNN Frameworks for image classification. TensorFlow
Classify Traffic Signs.
A practice for using CNN to recognize road signs.
Part of my Master Thesis in Autonomous Driving.
Traffic Sign Classification (GTSRB dataset) using Random Forest Classifier
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.
Convolutional Neural Networks (CNN) with Computer Vision (CV) for GTSRB Traffic Sign Classification
Open source neural network solutions for the GTSRB challenge
Training a VGG16 Network to Classify Traffic Signs using the German Traffic Sign Recognition Benchmark (GTSRB)
Detect and Analyze Trojan attacks on deep neural networks that are designed to be difficult to detect.
A CNN model to classify German traffic signs
Classify traffic signs by using the AlexNet and GoogLeNet architecture using GTSRB dataset and comparing the two
Building autonomous vehicles from the ground up!
Robust Transformer with Locality Inductive Bias and Feature Normalization (JESTECH 2023)
Fast and accurate ResNet for the GTSRB dataset
Dieses Projekt beschäftigt sich mit der Entwicklung eines flachen CNN zur Erkennung von Verkehrsschildern. Das Projekt beinhaltet alle dazu benötigten Programme und Tools.
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 ?
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