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Secured Perimeter with Electromagnetic Detection and Tracking with Drone Embedded and Static Cameras

Pedro Teixidó, Juan Antonio Gómez-Galán, Rafael Caballero, Francisco J. Pérez-Grau et al. • Sensors (2021)

Perimeter detection systems detect intruders penetrating protected areas, but modern solutions require the combination of smart detectors, information networks and controlling software to reduce false alarms and extend detection range. The ...

DOAJ Open Access (DOAJ) DOI: 10.3390/s21217379

Identifying people’s energy information needs through Energy Citizen Personas

Ajesh Kumar, Toni Kuronen, Bilal Naqvi, Salla Annala et al. • Energy Informatics (2026)

Abstract Energy Citizenship refers to individuals and communities participating, sometimes begrudgingly, in adopting energy solutions, whether sustainable or not. When enacted positively, it advances the green energy transition. There are s...

DOAJ Open Access (DOAJ) DOI: 10.1186/s42162-026-00691-0

Real-Time Weapon Detection and Suspect Face Capturing System Using YOLOv8

Chairina Ulfa, Muhammad Fikry, Hafizh Al Kautsar AIdilof • Journal of Applied Informatics and Computing (2026)

The rise of violent crimes involving sharp weapons and firearms in public spaces, including educational campuses, demands an automated real-time surveillance system to assist security personnel. This study proposes a web-based weapon detect...

DOAJ Open Access (DOAJ) DOI: 10.30871/jaic.v10i4.13454

Thorax-Segment- and Leg-Segment-Specific Motor Control for Adaptive Behavior

Elzbieta Hammel, Charalampos Mantziaris, Joscha Schmitz, Ansgar Büschges et al. • Frontiers in Physiology (2022)

We have just started to understand the mechanisms underlying flexibility of motor programs among segmental neural networks that control each individual leg during walking in vertebrates and invertebrates. Here, we investigated the mechanism...

DOAJ Open Access (DOAJ) DOI: 10.3389/fphys.2022.883858

Neural Networks for Pattern Recognition

Albert Nigrin • The MIT Press eBooks (1993)

In a simple and accessible way it extends embedding field theory into areas of machine intelligence that have not been clearly dealt with before. Neural Networks for Pattern Recognition takes the pioneering work in artificial neural network...

OPENALEX DOI: https://doi.org/10.7551/mitpress/4923.001.0001

Building neural networks

David M. Skapura (1995)

Foundations. Motivation. Neural-Network Fundamentals. Single Neuron Computations. Network Computations. Network Simulation. Foundations Summary. Suggested Readings. Bibliography. Paradigms. The Backpropagation Network. The Counterpropagatio...

OPENALEX

Bayesian Regularization of Neural Networks

Frank R. Burden, David Alan Winkler • Methods in molecular biology (2008)

Bayesian regularized artificial neural networks (BRANNs) are more robust than standard back-propagation nets and can reduce or eliminate the need for lengthy cross-validation. Bayesian regularization is a mathematical process that converts ...

OPENALEX DOI: https://doi.org/10.1007/978-1-60327-101-1_3