Abstract: For deploying deep neural networks on edge devices with limited resources, binary neural networks (BNNs) have attracted significant attention, due to their computational and memory ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification, according ...

Introduction: In recent years, advancements in machine learning and electronic stethoscope technology have enabled high-precision recording and analysis of lung sounds, significantly enhancing ...

Abstract: We present a general framework for training spiking neural networks (SNNs) to perform binary classification on multivariate time series, with a focus on step-wise prediction and high ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

The First Hospital of Hunan University of Chinese Medicine, Hunan University of Chinese Medicine, Changsha, China Background: Breast cancer remains the most prevalent malignancy in women globally, ...

A complete, professional neural network implementation built entirely from scratch using only NumPy for MNIST digit classification. This project achieves 98.06% test accuracy with a clean, ...