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

Esteban G. Contreras, Tomás Palominos, Álvaro Glavic, Andrea H. Brand et al. • Scientific Reports (2018)

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...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-018-31654-5

Formation of Cluster‐Structured Metallic Filaments in Organic Memristors for Wearable Neuromorphic Systems with Bio‐Mimetic Synaptic Weight Distributions

Uihoon Jung, Miseong Kim, Jaewon Jang, Jin‐Hyuk Bae et al. • Advanced Science (2024)

Abstract With increasing demand for wearable electronics capable of computing huge data, flexible neuromorphic systems mimicking brain functions have been receiving much attention. Despite considerable efforts in developing practical neural...

DOAJ Open Access (DOAJ) DOI: 10.1002/advs.202307494

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

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

Artificial neural networks

Kevin L. Moore • IEEE Potentials (1992)

Artificial neural networks are explained, and the different types are described. Three different tasks for which they are suitable are discussed. They are pattern classification and associative memory, self-organization and feature extracti...

OPENALEX DOI: https://doi.org/10.1109/45.127697

Neural networks for signal processing

Bart Kosko • CERN Document Server (European Organization for Nuclear Research) (1992)

This collection of essays explores neural networks applications in signal and image processing, function and estimation, robotics and control, associative memories, and electrical and optical networks. Intended as a companion to Neural Netw...

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Elements of Artificial Neural Networks

Kishan G. Mehrotra, Chilukuri Krishna Mohan, Sanjay Ranka • The MIT Press eBooks (1996)

Elements of Artificial Neural Networks provides a clearly organized general introduction, focusing on a broad range of algorithms, for students and others who want to use neural networks rather than simply study them. The authors, who have ...

OPENALEX DOI: https://doi.org/10.7551/mitpress/2687.001.0001

Connectomic insights into the impact of 1p/19q co-deletion in dominant hemisphere insular glioma patients

Zuo-cheng Yang, Bo-wen Xue, Xin-yu Song, Chuan-dong Yin et al. • Frontiers in Neuroscience (2024)

ObjectivesThis study aimed to elucidate the influences of 1p/19q co-deletion on structural connectivity alterations in patients with dominant hemisphere insular diffuse gliomas.MethodsWe incorporated 32 cases of left insular gliomas and 20 ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fnins.2024.1283518

A Comprehensive Analysis of Multilayer Community Detection Algorithms for Application to EEG-Based Brain Networks

Maria Grazia Puxeddu, Maria Grazia Puxeddu, Manuela Petti, Manuela Petti et al. • Frontiers in Systems Neuroscience (2021)

Modular organization is an emergent property of brain networks, responsible for shaping communication processes and underpinning brain functioning. Moreover, brain networks are intrinsically multilayer since their attributes can vary across...

DOAJ Open Access (DOAJ) DOI: 10.3389/fnsys.2021.624183

Fundamentals of Artificial Neural Networks

Mohamad H. Hassoun • Proceedings of the IEEE (1996)

From the Publisher: As book review editor of the IEEE Transactions on Neural Networks, Mohamad Hassoun has had the opportunity to assess the multitude of books on artificial neural networks that have appeared in recent years. Now, in Funda...

OPENALEX DOI: https://doi.org/10.1109/jproc.1996.503146

On neural networks.

Jiří Beneš • Czech digital mathematics library (1990)

JIŘÍ BENEŠTypical neural network models representing a broad survey of actual trends are considered in an unifying way as Complexes subject to specific control systems, called Formators which may have a two-level arrangement and incorporate...

OPENALEX Open Access

A Preliminary Study on the Auto-Segmentation of Targets and Organs at Risk in Pediatric Total Marrow and Lymphoid Irradiation

Zhihua Xie BS, Jinfeng Liu PhD, Lixia Hou MS, Haoran Feng MS et al. • Technology in Cancer Research & Treatment (2026)

Introduction Leukemia is one of the most prevalent cancers in children. The use of total marrow and lymphoid irradiation (TMLI) via helical tomotherapy (TOMO) as a conditioning regimen prior to bone marrow transplant (BMT) has been widely a...

DOAJ Open Access (DOAJ) DOI: 10.1177/15330338261426261

Understanding the role of autoencoders for stiff dynamical systems using information theory

Vijayamanikandan Vijayarangan, Harshavardhana A. Uranakara, Francisco E. Hernández–Pérez, Hong G. Im • Energy and AI (2025)

Using information theory, this study provides insights into how the construction of latent space of autoencoder (AE) using deep neural network (DNN) training finds a smooth (non-stiff) low-dimensional manifold in the stiff dynamical system....

DOAJ Open Access (DOAJ) DOI: 10.1016/j.egyai.2025.100567

A Review of Deep Learning Applications in Intrusion Detection Systems: Overcoming Challenges in Spatiotemporal Feature Extraction and Data Imbalance

Ya Zhang, Ravie Chandren Muniyandi, Faizan Qamar • Applied Sciences (2025)

In the rapid development of the Internet of Things (IoT) and large-scale distributed networks, Intrusion Detection Systems (IDS) face significant challenges in handling complex spatiotemporal features and addressing data imbalance issues. T...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15031552

SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks With at Most One Spike per Neuron

Milad Mozafari, Milad Mozafari, Mohammad Ganjtabesh, Abbas Nowzari-Dalini et al. • Frontiers in Neuroscience (2019)

Application of deep convolutional spiking neural networks (SNNs) to artificial intelligence (AI) tasks has recently gained a lot of interest since SNNs are hardware-friendly and energy-efficient. Unlike the non-spiking counterparts, most of...

DOAJ Open Access (DOAJ) DOI: 10.3389/fnins.2019.00625