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Logical Reasoning Based on Residual Attention Multi-scale Relation Network

XIONG Zhongmin, ZENG Qi, LU Peng, WANG Zhenhua, ZHENG Zongsheng • Jisuanji gongcheng (2023)

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...

DOAJ Open Access (DOAJ) DOI: 10.19678/j.issn.1000-3428.0064591

Evaluation of noise reduction methods in digital images: Classical filtering vs adaptive learning-based models

Subbulakshmi M, Mohammad Malik Mubeen S, Mohamed Ali E A • AIP Advances (2026)

Digital images acquired through imaging systems often lose their original fidelity due to various types of noise introduced during acquisition, storage, or transmission, consequently reducing clarity and adversely affecting subsequent image...

DOAJ Open Access (DOAJ) DOI: 10.1063/5.0332993

Humanized substitutions of Vmat1 in mice alter amygdala-dependent behaviors associated with the evolution of anxiety

Daiki X. Sato, Yukiko U. Inoue, Nahoko Kuga, Satoko Hattori et al. • iScience (2022)

Summary: The human vesicular monoamine transporter 1 (VMAT1) harbors unique substitutions (Asn136Thr/Ile) that affect monoamine uptake into synaptic vesicles. These substitutions are absent in all known mammals, suggesting their contributio...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.isci.2022.104800

On the character of consciousness

Arto eAnnila • Frontiers in Systems Neuroscience (2016)

The human brain is a particularly demanding system to infer its nature from observations. Thus, there is on one hand plenty of room for theorizing and on the other hand a pressing need for a rigorous theory. We apply statistical mechanics o...

DOAJ Open Access (DOAJ) DOI: 10.3389/fnsys.2016.00027

How structure determines correlations in neuronal networks.

Volker Pernice, Benjamin Staude, Stefano Cardanobile, Stefan Rotter • PLoS Computational Biology (2011)

Networks are becoming a ubiquitous metaphor for the understanding of complex biological systems, spanning the range between molecular signalling pathways, neural networks in the brain, and interacting species in a food web. In many models, ...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pcbi.1002059

Digital Local Return Services and Purchase Intention in Cross-Border E-Commerce: A Risk–Trust Perspective

Xianfa Shi, Miao Su, Keun-sik Park • Journal of Theoretical and Applied Electronic Commerce Research (2026)

Cross-border e-commerce offers consumers broader product access, yet uncertainty surrounding returns continues to suppress online purchase decisions. This study conceptualizes digital local return services as a digital assurance mechanism i...

DOAJ Open Access (DOAJ) DOI: 10.3390/jtaer21060165

Neural networks at work

Dan W. Hammerstrom • IEEE Spectrum (1993)

The benefits of neural networks and the types of application for which they are suited are outlined. Four representative applications are described in enough detail to show how they work. They are character recognition, function estimation,...

OPENALEX DOI: https://doi.org/10.1109/6.214579

Neural Networks and Analog Computation

Hava T. Siegelmann • Birkhäuser Boston eBooks (1999)

The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer consisting of multiple assemblies of basic processors interconnecte...

OPENALEX DOI: https://doi.org/10.1007/978-1-4612-0707-8

An Introduction to Neural Networks

Kevin Robert Gurney • CRC Press eBooks (2018)

Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counte...

OPENALEX DOI: https://doi.org/10.1201/9781315273570

Working with neural networks

Dan W. Hammerstrom • IEEE Spectrum (1993)

As explanation of how neural networks operate is given. Programming of neural networks and regular computers is compared. Matching a neural network to an application is discussed. Designing and training a neural network is examined.>...

OPENALEX DOI: https://doi.org/10.1109/6.222230

Introduction to the Artificial Neural Networks

Andrej Krenker, Janez Bešter, Andrej Kos • InTech eBooks (2011)

An Artificial Neural Network (ANN) is a mathematical model that tries to simulate the structure and functionalities of biological neural networks. Basic building block of every artificial neural network is artificial neuron, that is, a simp...

OPENALEX cc-by-nc-sa DOI: https://doi.org/10.5772/15751

Neural networks for nonlinear programming

Michael Peter Kennedy, Leon Ong Chua • IEEE Transactions on Circuits and Systems (1988)

The dynamics of the modified canonical nonlinear programming circuit are studied and how to guarantee the stability of the network's solution. By considering the total cocontent function, the solution of the canonical nonlinear programming ...

OPENALEX DOI: https://doi.org/10.1109/31.1783