IEEE

Hybrid Quantum Network for classification of finance and MNIST data

Abstract: In the ongoing era of noisy intermediate scaled quantum computers, one of the possible applications to search for an advantage of quantum computing is machine learning. Here we report about ...
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 ...
Frontiers

Memristor Based Binary Convolutional Neural Network Architecture With Configurable Neurons

1 College of Electronic Science and Technology, National University of Defense Technology, Changsha, China 2 College of Electrical and Information Engineering, Hunan University, Changsha, China The ...
Analytics India Magazine

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

In Computer Vision, specifically, Image processing has become more efficient with the use of deep learning algorithms. To show the performance of these neural networks some basic preprocessed datasets ...