IEEE

Privacy-Preserving Image Classification based on Federated Learning with Hybrid CNNs Model on MNIST Data

Abstract: Background: Machine learning (ML) privacy problems have prompted the creation of privacy-preserving methods, one of which is Federated Learning (FL), which has emerged as an important ...
GitHub

Using LDA, SVM, and Decision Trees to deal with MNIST data set

This project involves the classification of handwritten digits using three different classifiers: Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), and Decision Trees. The goal is to ...
GitHub

iid mnist data set accuracy does not increase

Hello, in the latest code, there is still an extremely slow increase in average test accuracy at this time the required learning rate is 0.2 but the AUC is increasing rapidly. This problem occurs in ...
Visual Studio Magazine

Convolutional Neural Networks for MNIST Data Using PyTorch

Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset. The "Hello World" of image ...
Visual Studio Magazine

Convolutional Neural Networks for MNIST Data Using PyTorch

The "Hello World" of image classification is a convolutional neural network (CNN) applied to the MNIST digits dataset. A good way to see where this article is headed is to take a look at the ...
Frontiers

Memristor Based Binary Convolutional Neural Network Architecture With Configurable Neurons

The memristor-based convolutional neural network (CNN) gives full play to the advantages of memristive devices, such as low power consumption, high integration density, and strong network recognition ...
Analytics India Magazine

6 MNIST Image Datasets That Data Scientists Should Be Aware Of (With Python Implementation)

In today’s article, we’ll be talking about the very basic and primarily the most curated datasets used for deep learning in computer vision.To show the performance of these neural networks some basic ...