Academic Articles & Research Papers

Artificial neural networks in medical diagnosis

An extensive amount of information is currently available to clinical specialists, ranging from details of clinical symptoms to various types of biochemical data and outputs of imaging devices. Each type of data provides information that mu...

Neural Networks Theory

Artificial Neural Networks: An Introduction

This tutorial text provides the reader with an understanding of artificial neural networks (ANNs) and their application, beginning with the biological systems which inspired them, through the learning methods that have been developed and th...

Neural Networks and Statistical Learning

A neural network model for bankruptcy prediction

A neural network model is developed for prediction of bankruptcy, and it is tested using financial data from various companies. The same set of data is analyzed using a more traditional method of bankruptcy prediction, multivariate discrimi...

Neural network ensembles

Several means for improving the performance and training of neural networks for classification are proposed. Crossvalidation is used as a tool for optimizing network parameters and architecture. It is shown that the remaining residual gener...

Boosting Neural Networks

Boosting is a general method for improving the performance of learning algorithms. A recently proposed boosting algorithm, AdaBoost, has been applied with great success to several benchmark machine learning problems using mainly decision tr...

Intrusion Detection with Neural Networks

With the rapid expansion of computer networks during the past few years, security has become a crucial issue for modern computer systems. A good way to detect illegitimate use is through monitoring unusual user activity. Methods of intrusio...

Survey on categorical data for neural networks

Abstract This survey investigates current techniques for representing qualitative data for use as input to neural networks. Techniques for using qualitative data in neural networks are well known. However, researchers continue to discover n...

Adjustment of the Minimum Spouting Velocity in a Conical Spouted Bed from Artificial Neural Networks

The minimum spouting velocity is one of the fundamental parameters in the application of the conical spouted bed pyrolysis, gasification and combustion, therefore it is necessary the adequate calculation and the use of a correlation with go...

CG-DINO: Improved Network for Small Object Detection in Uncrewed Aerial Vehicle Imagery Based on DINO

Object detection in uncrewed aerial vehicle (UAV) acquired images remains a challenging task due to extreme scale variation, dense object layouts, and complex backgrounds, etc. Although convolutional neural networks (CNNs), transformers, an...

Dynamic Sign Language Recognition in Bahasa using MediaPipe, Long Short-Term Memory, and Convolutional Neural Network

Background: Communication is important for everyone, including individuals with hearing and speech impairments. For this demographic, sign language is widely used as the primary medium of communication with others who share similar conditio...

Incorporating structural plasticity into self-organization recurrent networks for sequence learning

IntroductionSpiking neural networks (SNNs), inspired by biological neural networks, have received a surge of interest due to its temporal encoding. Biological neural networks are driven by multiple plasticities, including spike timing-depen...

Predicting air quality index using artificial neural network: a case study of the Coimbatore region

Abstract This study predicts the Air Quality Index (AQI) in the Coimbatore region using Artificial Neural Networks (ANN) to enhance air quality management and environmental science. The researchers measured six input variables over a two-ye...

Principles of Artificial Neural Networks

The book should serve as a text for a university graduate course or for an advanced undergraduate course on neural networks in engineering and computer science departments. It should also serve as a self-study course for engineers and compu...

Chaotic Neural Networks

Probabilistic Neural Networks

The Handbook of brain theory and neural networks

A new, dramatically updated edition of the classic resource on the constantly evolving fields of brain theory and neural networks. Dramatically updating and extending the first edition, published in 1995, the second edition of The Handbook ...

Fundamentals of neural networks

Image processing with neural networks—a review