Academic Articles & Research Papers

Network dynamics underlying OFF responses in the auditory cortex

Across sensory systems, complex spatio-temporal patterns of neural activity arise following the onset (ON) and offset (OFF) of stimuli. While ON responses have been widely studied, the mechanisms generating OFF responses in cortical areas h...

A Multi-Class ECG Signal Classifier Using a Binarized Depthwise Separable CNN with the Merged Convolution–Pooling Method

Binarized convolutional neural networks (bCNNs) are favored for the design of low-storage, low-power cardiac arrhythmia classifiers owing to their high weight compression rate. However, multi-class classification of ECG signals based on bCN...

Surrogate Modeling of the Electric Field in the End-Winding Region of Pumped-Storage Generator Stators Based on Deep Neural Networks

The end-winding insulation structure of stator windings in pumped-storage generator units is complex, with pronounced electric field concentration under out-of-phase conditions, making them critical concerns in insulation design and conditi...

Applying Neural Networks: A Practical Guide

Techniques for building neural networks: introduction what are neural networks? how does neural computing differ from traditional programming? how are neural networks built? how do neural networks learn? what do I need to build an MLP? the ...

Neural Networks for RF and Microwave Design

From the Publisher: Discover the new, unconventional alternatives for conquering RF and microwave design and modeling problems using neural networks — information processing systems that can learn, generalize, and even allow model developm...

SPIKING NEURAL NETWORKS

Most current Artificial Neural Network (ANN) models are based on highly simplified brain dynamics. They have been used as powerful computational tools to solve complex pattern recognition, function estimation, and classification problems. A...

Artificial neural network and wavelet neural network approaches for modelling of a solar air heater

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...

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...

An Improved Convolutional Neural Network (CNN) for Disease Detection and Diagnosis for Multi-crop Plants

Agriculture is one of the largest sectors that contribute to the economic growth of countries, including Malaysia. However, plant diseases affect the quality of the harvest and impede farmers’ maximum yield output. Therefore, early detectio...

A new perspective on delusional states: Evidence for claustrum involvement

Delusions are a hallmark positive symptom of schizophrenia, although they are also associated with a wide variety of other psychiatric and neurological disorders. The heterogeneity of clinical presentation and underlying disease, along with...

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...

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...

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 ...

Overcoming catastrophic forgetting in neural networks

The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitabl...

Neural Networks for Chemists

In recent years, breakthroughs in artificial intelligence (AI) have dramatically transformed many fields. Developments in neural networks primarily drive the advances. These powerful models have demonstrated unprecedented capabilities in le...

Modeling of Self-Aligned Selector Based on Ultra-Thin Metal Oxide for Resistive Random-Access Memory (RRAM) Crossbar Arrays

Resistive random-access memory (RRAM) is a crucial element for next-generation large-scale memory arrays, analogue neuromorphic computing and energy-efficient System-on-Chip applications. For these applications, RRAM elements are arranged i...

The transcription factor SoxD controls neuronal guidance in the Drosophila visual system

Abstract Precise control of neurite guidance during development is essential to ensure proper formation of neuronal networks and correct function of the central nervous system (CNS). How neuronal projections find their targets to generate a...

Logical Reasoning Based on Residual Attention Multi-scale Relation Network

Logical reasoning is the ability to perceive patterns and connections between visual elements. Endowing computers with human-like reasoning ability is a critical area of research；state-of-the-art deep neural networks have achieved superhuma...