There are 4 repositories under lenet-5 topic.
My works for EE 569 - Digital Image Processing - Spring 2018 - Graduate Coursework at USC - Dr. C.-C. Jay Kuo
Hand gesture interface for Desktop PC and Raspberry Pi.
Collection of tensorflow notebooks tutorials for implementing some basic Deep Learning architectures.
Implementation of LeNet-5 with keras
Deep learning model implementation from scratch using pytorch
Image classification models on CIFAR10 dataset using pytorch
In this repository you will find everything you need to know about Convolutional Neural Network, and how to implement the most famous CNN architectures in both Keras and PyTorch. (I'm working on implementing those Architectures using MxNet and Caffe)
A library of VHDL components for Neural Networks
Pure numpy implementation of LeNet5, to help you understand how CNN works.
CNN-based image retrieval with TensorFlow and Keras
Centralized Federated Learning using WebSockets and TensorFlow
Camera based ROS line follower node
PyTorch implementation of LeNet5
Implement LeNet-5 on MNIST dataset.
Pre-trained 3D CNNs
HandwrittenDigitRecognition、FlowerRecognition、LotteryOnline and ChatInWeb based on Tornado and Tensorflow
Contains python files to break simple captchas.
Convolutional Neural Networks repository for all projects of Course 4 of 5 of the Deep Learning Specialization covering CNNs and classical architectures like LeNet-5, AlexNet, GoogleNet Inception Network, VGG-16, ResNet, 1x1 Convos, OverFeat, R-CNN, Fast R-CNN, Faster R-CNN, YOLO, YOLO9000, DeepFace, FaceNet and Neural Style Transfer.
LeNet-5 Convolution Neural Network built primarily using NumPy and applied on the MNIST Handwritten Digit Dataset
This repository aims to provide a valuable resource for individuals interested in learning and mastering TensorFlow, an open-source machine learning framework developed by Google.
LeNet5 from Scratch
Implementation of LeNet-5 over MNIST Dataset using PyTorch from Scratch, presenting an accuracy of ~99%
Utilizing various CNN architectures to perform digit recognition on the MNIST Dataset.
Build a Convolutional Neural Network (CNN) that recognizes traffic signs.
Using tensorflow to build the lenet-5 network proposed by Yann LeCun.
Variants of LeNet-like architectures with increased accuracy at MNIST dataset by using Absolute activation function
FYP project. A VerilogHDL based hardware accelerator.
LeNet-5 is proposed by Yann LeCun in 1988. This model is a pioneer of image recognition models using convolutional neural networks. I want to reproduce this historical model as it was in 1998 with PyTorch
cifar 10 dataset and minist dataset
Re-implement lenet with pytorch lightning (coursework)