lenet5

PyTorch implementation of LeNet-5 with live visualization

Deep Learning code

Summary & Implementation of Deep Learning research paper in Tensorflow/Pytorch.

Replace FC2, LeNet-5, VGG, Resnet, Densenet's full-connected layers with MPO

Pytorch implementation(LeNet, VGGNet, GAN, UNet, Mask R-CNN, ...)

基于Pytorch复现的Yann LeCun大佬于1998年提出的LeNet5模型。

Numpy implementation of deep learning

Convolutional Neural Network implemenation from scratch in python numpy

A simple and extensible image recognition neural network framework

5-stage RISC-V RV32I processor + INT8 CNN hardware accelerator SoC for edge AI - synthesized on Xilinx Artix-7 at 100 MHz RTL in Verilog 2001

CNN architectures in C++

lenet5的tensorflow实现

LeNet5 on MNIST with SGD and Adam

Simple LeNet5 for MNIST dataset with PyTorch and achieves 99.13% accuracy on the test data.

Training and testing various CNN models for image classification.

Part 1 of Visual Scrambling — LeNet-5 architecture reconstruction Pytorch with convolution geometry, RBF function, pooling and broadcasting explanation

Implementation and comparison of SVM and LeNet5 on MNIST

Convolutional Neural Net to Classify Traffic Signs

This repository contains implementation of some deep neural networks by Keras.

MLP, LeNet-5 CNN and GRU Seq2Seq built in PyTorch, with convolution and pooling implemented by hand and verified against the library. Includes the full scientific report and all result figures.