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.

Neural network accelerator project completed using hls4ml tool.

numpy lenet implementation.

Experimenting with MNIST using the MXNet machine learning framework

使用TensorFlow简单实现LeNet

Handwritten Digit Recognition - MNIST

Simple example of a neural network with Tensorflow plus a toy example using MNIST and LeNet architecture with Keras

Machine Learning Course Design

~99.50% accuracy on MNIST 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

Implementation of LeNet-5 on MNIST Dataset in PyTorch

Implementation of LeNet-5, AlexNet, VGG-16 as explained by Andrew NG in Deeplearning.AI

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.