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Academic Articles & Research Papers
Showing 20 of 2,633 academic articles
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
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
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
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
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
Timothy D. Masters (1993)
This text serves as a cookbook for neural network solutions to practical problems using C++. It will enable those with moderate programming experience to select a neural network model appropriate to solving a particular problem, and to prod...
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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...
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DOI: https://doi.org/10.1007/978-1-4612-0707-8
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...
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DOI: https://doi.org/10.1201/9781315273570
H. K. D. H. Bhadeshia • ISIJ International
(1999)
There are difficult problems in materials science where the general concepts might be understood but which are not as yet amenable to scientific treatment. We are at the same time told that good engineering has the responsibility to reach o...
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Open Access
DOI: https://doi.org/10.2355/isijinternational.39.966
Keiron O’Shea, Ryan Nash • arXiv (Cornell University)
(2015)
The field of machine learning has taken a dramatic twist in recent times, with the rise of the Artificial Neural Network (ANN). These biologically inspired computational models are able to far exceed the performance of previous forms of art...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1511.08458
Francisco J Zamora-Martínez, Salvador España-Boquera, Maria Jose Castro-Bleda, Adrian Palacios-Corella • PLoS ONE
(2018)
This paper presents a new method to reduce the computational cost when using Neural Networks as Language Models, during recognition, in some particular scenarios. It is based on a Neural Network that considers input contexts of different le...
DOAJ
Open Access (DOAJ)
DOI: 10.1371/journal.pone.0200884
J. J. Hopfield • IEEE Circuits and Devices Magazine
(1988)
Examines the following questions associated with artificial neural networks: why people are interested in artificial neural networks; what artificial neural networks are, from the point of view of electronic circuits, and how they work; how...
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DOI: https://doi.org/10.1109/101.8118
Fathaddin Muhammad Taufiq, Sari Alvita Kumala, Sutansyah Daddy, Ulfah Baiq Maulinda et al. • E3S Web of Conferences
(2024)
Relative permeability is a substantial parameter for estimating multi-phase fluid flow in porous rocks. It is a complex physical property that is influenced by the behavior and interactions between the fluid and rock phases. Relative permea...
DOAJ
Open Access (DOAJ)
DOI: 10.1051/e3sconf/202450003019
Jiquan Ngiam, Adam Coates, Ahbik Lahiri, Bobby Prochnow et al. • International Conference on Machine Learning
(2011)
The predominant methodology in training deep learning advocates the use of stochastic gradient descent methods (SGDs). Despite its ease of implementation, SGDs are difficult to tune and parallelize. These problems make it challenging to dev...
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Zahra Zamanzadeh Darban, Geoffrey I. Webb, Shirui Pan, Charų C. Aggarwal et al. • ACM Computing Surveys
(2024)
Time series anomaly detection is important for a wide range of research fields and applications, including financial markets, economics, earth sciences, manufacturing, and healthcare. The presence of anomalies can indicate novel or unexpect...
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DOI: https://doi.org/10.1145/3691338
Umara Zafar, Mubeen Ghafoor, Tehseen Zia, Ghufran Ahmed et al. • EURASIP Journal on Image and Video Processing
(2019)
Abstract Recognition of facial images is one of the most challenging research issues in surveillance systems due to different problems including varying pose, expression, illumination, and resolution. The robustness of recognition method st...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s13640-019-0406-y
Camille R. Reaux, Shelby A. Meche, Jordan M. Grider, Soundharya Dhanabal et al. • Frontiers in Education
(2025)
Given the exponential growth of biochemical data and deep effect of computational methods on life sciences, there is a need to rethink undergraduate curricula. A project-oriented learning approach based on the Triangular Spatial Relationshi...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/feduc.2024.1455173
Z. Karami • Fanāvarī-i āmūzish
(2023)
Background and Objectives: In order to solve the problem of education in complex and unstructured domains, Spiro and his colleagues proposed the theory of cognitive flexibility, in which they advocated multiple forms of pedagogical models, ...
DOAJ
Open Access (DOAJ)
DOI: 10.22061/tej.2023.9686.2885
Siwei Yu, Jianwei Ma • Reviews of Geophysics
(2021)
Abstract Recently deep learning (DL), as a new data‐driven technique compared to conventional approaches, has attracted increasing attention in geophysical community, resulting in many opportunities and challenges. DL was proven to have the...
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DOI: https://doi.org/10.1029/2021rg000742
Lucas Prado Osco, José Marcato, Ana Paula Marques Ramos, Lúcio André de Castro Jorge et al. • International Journal of Applied Earth Observation and Geoinformation
(2021)
Deep Neural Networks (DNNs) learn representation from data with an impressive capability, and brought important breakthroughs for processing images, time-series, natural language, audio, video, and many others. In the remote sensing field, ...
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DOI: https://doi.org/10.1016/j.jag.2021.102456