IEEE

Privacy-Preserving Self-Supervised Learning for Secure Image Processing: A BYOL-Based Framework for MNIST and Chest X-ray Data

Abstract: The increasing use of high-dimensional imaging in medical AI raises significant privacy and security concerns. This paper presents a Bootstrap Your Own Latent (BYOL)-based self-supervised ...
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 ...
Frontiers

TAIM: Tool for Analyzing Root Images to Calculate the Infection Rate of Arbuscular Mycorrhizal Fungi

Arbuscular mycorrhizal fungi (AMF) infect plant roots and are hypothesized to improve plant growth. Recently, AMF is now available for axenic culture. Therefore, AMF is expected to be used as a ...
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 ...
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 ...