IEEE

Image Classification using Quantum Convolutional Neural Network (QCNN)

Abstract: Convolutional Neural Networks (CNNs) are extensively utilized for image classification due to their ability to exploit data correlations effectively. However, traditional CNNs encounter ...
GitHub

number-classification

A public API for HNG Stage 1 task that classifies a given number by identifying its mathematical properties (prime, perfect, Armstrong, parity, digit sum) and retrieves a fun fact using the Numbers ...
CNN

How To Use Technology and Not Lose Our Minds

'Sure. Okay, I think there's three things that we used to do in what we could laughably call the olden days that I would suggest we all do, not just parents. Three things are important. One is ...
Federal Register

Medical Devices; Orthopedic Devices; Classification of Orthopedic Manual Surgical Instrumentation for Use With Total Disc Replacement Devices

This document has been published in the Federal Register. Use the PDF linked in the document sidebar for the official electronic format.
Frontiers

Novel deep learning for multi-class classification of Alzheimer’s in disability using MRI datasets

Introduction: Alzheimer’s disease (AD) is one of the most common neurodegenerative disabilities that often leads to memory loss, confusion, difficulty in language and trouble with motor coordination.
GitHub

MinOS-WJ/CNN-MNIST

• Architecture: 4-layer CNN (convolutional layers with 32, 64, 128, and 256 filters) → Max pooling → Dropout → Fully connected layers. • Training: Dataset: MNIST (28×28 grayscale digits).
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 ...