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Academic Articles & Research Papers
Showing 20 of 227 academic articles
Alexander Craik, Yongtian He, Jose Luis Contreras-Vidal • Journal of Neural Engineering
(2019)
OBJECTIVE: Electroencephalography (EEG) analysis has been an important tool in neuroscience with applications in neuroscience, neural engineering (e.g. Brain-computer interfaces, BCI's), and even commercial applications. Many of the analyti...
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DOI: https://doi.org/10.1088/1741-2552/ab0ab5
Mufti Mahmud, M. Shamim Kaiser, Amir Hussain, Stefano Vassanelli • IEEE Transactions on Neural Networks and Learning Systems
(2018)
Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body...
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Open Access
DOI: https://doi.org/10.1109/tnnls.2018.2790388
Travers H. Ching, Daniel Scott Himmelstein, Brett K. Beaulieu‐Jones, Alexandr A. Kalinin et al. • Journal of The Royal Society Interface
(2018)
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and m...
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DOI: https://doi.org/10.1098/rsif.2017.0387
PMC: 5938574
Ruud J. G. van Sloun, Regev Cohen, Yonina C. Eldar • Proceedings of the IEEE
(2019)
In this article, we consider deep learning strategies in ultrasound systems, from the front end to advanced applications. Our goal is to provide the reader with a broad understanding of the possible impact of deep learning methodologies on ...
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Open Access
DOI: https://doi.org/10.1109/jproc.2019.2932116
Skorupka KA, Matsuoka K, Imahashi M, Yokomaku Y et al. • Nature communications
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.1038/s41467-026-78197-2
PMC: PMC13737106
Natasha Dropka, Stefan Ecklebe, Martin Holena • Crystals
(2021)
The aim of this study was to assess the aptitude of the recurrent Long Short-Term Memory (LSTM) neural networks for fast and accurate predictions of process dynamics in vertical-gradient-freeze growth of gallium arsenide crystals (VGF-GaAs)...
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Open Access (DOAJ)
DOI: 10.3390/cryst11020138
Banu Torun Acar, Tahir Kansu Bozkurt, Selin Tuğtan, Suphi Acar • Türk Oftalmoloji Dergisi
(2014)
Objectives: To report the intraoperative and postoperative follow-up complications and management of these in deep anterior lamellar
keratoplasty (DALK) surgery.
Materials and Methods: Two hundred eighty-four eyes of 252 patients followed...
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Open Access (DOAJ)
DOI: 10.4274/tjo.02259
Conrad H. Stansbury, Alessandra Lanzara • Software
(2023)
Scientific data acquisition is a problem domain that has been underserved by its computational tools despite the need to efficiently use hardware, to guarantee validity of the recorded data, and to rapidly test ideas by configuring experime...
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Open Access (DOAJ)
DOI: 10.3390/software2010005
Orges Koci, Richard K. Russell, M. Guftar Shaikh, Christine Edwards et al. • Microbiome
(2024)
Abstract Background Shotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, t...
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Open Access (DOAJ)
DOI: 10.1186/s40168-024-01834-9
Yajing Tian, Yuyang Wang, Shasha Yin, Jia Lu et al. • Energies
(2024)
U-tube steam generators (UTSGs) are crucial in nuclear power plants, serving as the interface between the primary and secondary coolant loops. UTSGs ensure efficient heat exchange, operational stability, and safety, directly impacting the p...
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Open Access (DOAJ)
DOI: 10.3390/en17163916
Iason Batzianoulis, Fumiaki Iwane, Shupeng Wei, Carolina Gaspar Pinto Ramos Correia et al. • Communications Biology
(2021)
Teaching an assistive robotic manipulator to move objects in a cluttered table requires demonstrations from expert operators, but what if the experts are individuals with motor disabilities? Batzianoulis et al. propose a learning approach w...
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Open Access (DOAJ)
DOI: 10.1038/s42003-021-02891-8
Paolo Graniero, Paolo Graniero, Mark Khenkin, Hans Köbler et al. • Frontiers in Energy Research
(2023)
Perovskite solar cells are the most dynamic emerging photovoltaic technology and attracts the attention of thousands of researchers worldwide. Recently, many of them are targeting device stability issues–the key challenge for this technolog...
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Open Access (DOAJ)
DOI: 10.3389/fenrg.2023.1118654
Jerry Alan Fails, Dan R. Olsen • ACM International Conference on Intelligent User Interfaces (IUI)
(2003)
Perceptual user interfaces (PUIs) are an important part of ubiquitous computing. Creating such interfaces is difficult because of the image and signal processing knowledge required for creating classifiers. We propose an interactive machine...
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DOI: https://doi.org/10.1145/604045.604056
Binayak Panda, Sudhanshu Shekhar Bisoyi, Sidhanta Panigrahy • PeerJ Computer Science
(2023)
Dependence on the internet and computer programs demonstrates the significance of computer programs in our day-to-day lives. Such demands motivate malware developers to create more malware, both in terms of quantity and variety. Researchers...
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Open Access (DOAJ)
DOI: 10.7717/peerj-cs.1677
Sridhar Chandrasekaran, Yao-Feng Chang, Firman Mangasa Simanjuntak • Nanomaterials
(2026)
The memristor has long been known as a nonvolatile memory technology alternative and has recently been explored for neuromorphic computing, owing to its capability to mimic the synaptic plasticity of the human brain. The architecture of a m...
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Open Access (DOAJ)
DOI: 10.3390/nano16030179
Matthias S. Treder • Frontiers in Neuroscience
(2020)
MVPA-Light is a MATLAB toolbox for multivariate pattern analysis (MVPA). It provides native implementations of a range of classifiers and regression models, using modern optimization algorithms. High-level functions allow for the multivaria...
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Open Access (DOAJ)
DOI: 10.3389/fnins.2020.00289
Joshua I. Glaser, Ari S. Benjamin, Raeed H. Chowdhury, Matthew G. Perich et al. • eNeuro
(2020)
Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods. Modern machine learning tools, which are versatile and easy to use, have the potential to significantly improve deco...
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DOI: https://doi.org/10.1523/eneuro.0506-19.2020
PMC: 7470933
Emily K. Makowski, Patrick C. Kinnunen, Jie Huang, Lina Wu et al. • Nature Communications
(2022)
Optimising antibody properties such as affinity can be detrimental to other key properties. Here the authors use machine learning to simplify the identification of antibodies with co-optimal levels of affinity and specificity for a clinical...
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Open Access (DOAJ)
DOI: 10.1038/s41467-022-31457-3
Bernd Bischl, Michel Lang, Lars Kotthoff, Patrick Schratz et al. (2013)
Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensiti...
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Open Access
DOI: https://doi.org/10.32614/cran.package.mlr
T. Nageshkumar, Prateek Shrivastava, L. Ammayapan, Manisha Jagadale et al. • Journal of Natural Fibers
(2025)
Machine learning model coupled with graphical user interface was developed to predict mechanical properties of flax fiber. The experiment was conducted using test setup which applies constant rate of loading (CRL). Flax fiber was tested und...
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Open Access (DOAJ)
DOI: 10.1080/15440478.2025.2502662