Implementation of LeNet-5, AlexNet, VGG-16 as explained by Andrew NG in Deeplearning.AI
-
Updated
Jul 29, 2018 - Jupyter Notebook
Implementation of LeNet-5, AlexNet, VGG-16 as explained by Andrew NG in Deeplearning.AI
Implementation of LeNet DNN Model
numpy lenet implementation.
Experimenting with MNIST using the MXNet machine learning framework
~99.50% accuracy on MNIST in PyTorch
Implementation of LeNet-5 on MNIST Dataset in PyTorch
Lenet customisation with more filters, 3*3 filters, Relu activation fucntion
The MNIST classification model using the LeNet network with Tensorflow and Keras
Handwritten Digit Recognition - MNIST
A Pytorch implementation of a customized LeNet-5 algorithm designed to give best results on the classic MNIST dataset.
Classify images of handwritten digits with a LeNet Convolutional Neural Network and a Deep Neural Network
Create a LeNet convolutional neural network to classify images of road signs.
This framework was part of the Diploma thesis titled "Architectures and Implementations of the Neural Network LeNet-5 in FPGAs". The main goal of this thesis was to create a LeNet-5 implementation in an FPGA development board, but also form a reusable framework/workflow which can be modified to model and develop other Neural Networks as well.
Image processing library
Add a description, image, and links to the lenet-mnist topic page so that developers can more easily learn about it.
To associate your repository with the lenet-mnist topic, visit your repo's landing page and select "manage topics."