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Academic Articles & Research Papers
Showing 20 of 621 academic articles
Samira Pouyanfar, Saad B Sadiq, Yilin Yan, Haiman Tian et al. • ACM Computing Surveys
(2018)
The field of machine learning is witnessing its golden era as deep learning slowly becomes the leader in this domain. Deep learning uses multiple layers to represent the abstractions of data to build computational models. Some key enabler d...
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DOI: https://doi.org/10.1145/3234150
Seonwoo Min, Byunghan Lee, Sungroh Yoon • Briefings in Bioinformatics
(2016)
In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-th...
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Open Access
DOI: https://doi.org/10.1093/bib/bbw068
Gabriel de Sousa Meira, João Victor Ferreira Guedes, Edilson de Souza Bias • Drones
(2024)
The use of geotechnologies in the field of diagnostic engineering has become ever more present in the identification of pathological manifestations in buildings. The implementation of Unmanned Aerial Vehicles (UAVs) and embedded sensors has...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/drones8070341
Mohammed Javeed Zaki, Wagner Meira • Cambridge University Press eBooks
(2020)
The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business an...
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DOI: https://doi.org/10.1017/9781108564175
Clara Muñoz-Castro, Ayush Noori, Colin G. Magdamo, Zhaozhi Li et al. • Journal of Neuroinflammation
(2022)
Abstract Background Astrocytes and microglia react to Aβ plaques, neurofibrillary tangles, and neurodegeneration in the Alzheimer’s disease (AD) brain. Single-nuclei and single-cell RNA-seq have revealed multiple states or subpopulations of...
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Open Access (DOAJ)
DOI: 10.1186/s12974-022-02383-4
Yunji Chen, Tao Luo, Shaoli Liu, Shijin Zhang et al. • IEEE/ACM International Symposium on Microarchitecture (MICRO)
(2014)
Many companies are deploying services, either for consumers or industry, which are largely based on machine-learning algorithms for sophisticated processing of large amounts of data. The state-of-the-art and most popular such machine-learni...
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DOI: https://doi.org/10.1109/micro.2014.58
Stephen Marsland (2009)
Traditional books on machine learning can be divided into two groups - those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is r...
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Alexander I. Kochegurov, Vladislav I. Denisov, Elizaveta A. Zadorozhnykh • Известия Томского политехнического университета: Инжиниринг георесурсов
(2024)
Relevance. Core studies in the oil and gas industry allow us to obtain some filtration and capacity characteristics of rocks, as well as to give an idea of the composition and structure of the subsoil. This information is extremely importan...
DOAJ
Open Access (DOAJ)
DOI: 10.18799/24131830/2024/9/4792
Masoud Mahdianpari, Bahram Salehi, Mohammad Rezaee, Fariba Mohammadimanesh et al. • Remote Sensing
(2018)
Despite recent advances of deep Convolutional Neural Networks (CNNs) in various computer vision tasks, their potential for classification of multispectral remote sensing images has not been thoroughly explored. In particular, the applicatio...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs10071119
Shihao Gu, Bryan Kelly, Dacheng Xiu • National Bureau of Economic Research
(2018)
We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premia.We demonstrate large economic gains to investors using machine learning forecasts, in some cases...
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Open Access
DOI: https://doi.org/10.3386/w25398
Nishant Shukla • CERN Document Server (European Organization for Nuclear Research)
(2018)
Summary Machine Learning with Tensor Flow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding Tensor Flow with Python. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub forma...
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Grace W. Lindsay • Frontiers in Computational Neuroscience
(2020)
Attention is the important ability to flexibly control limited computational resources. It has been studied in conjunction with many other topics in neuroscience and psychology including awareness, vigilance, saliency, executive control, an...
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cc-by
DOI: https://doi.org/10.3389/fncom.2020.00029
PMC: 7177153
Nicholas M. Ball, Robert J. Brunner • International Journal of Modern Physics D
(2010)
We review the current state of data mining and machine learning in astronomy. Data Mining can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding ...
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Open Access
DOI: https://doi.org/10.1142/s0218271810017160
Yernazar Bolat, Iain Murray, Yifei Ren, Nasim Ferdosian • Sensors
(2025)
The growing adoption of IoT applications has led to increased use of low-power microcontroller units (MCUs) for energy-efficient, local data processing. However, deploying deep neural networks (DNNs) on these constrained devices is challeng...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s25154595
Ziru Fu, Yu Cheng Hsu, Christian S Chan, Chaak Ming Lau et al. • Journal of Medical Internet Research
(2024)
BackgroundSentiment analysis is a significant yet difficult task in natural language processing. The linguistic peculiarities of Cantonese, including its high similarity with Standard Chinese, its grammatical and lexical uniqueness, and its...
DOAJ
Open Access (DOAJ)
DOI: 10.2196/51069
Jörn Lötsch, Alfred Ultsch • Pain
(2017)
1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...
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cc-by-nc-nd
DOI: https://doi.org/10.1097/j.pain.0000000000001118
PMC: 5895117
Yagang Zhang • InTech eBooks
(2010)
Machine learning techniques have the potential of alleviating the complexity of knowledge acquisition. This book presents today’s state and development tendencies of machine learning. It is a multi-author book. Taking into account the large...
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Open Access
DOI: https://doi.org/10.5772/217
James L. Melville, Edmund K. Burke, Jonathan D. Hirst • Combinatorial Chemistry & High Throughput Screening
(2009)
In this review, we highlight recent applications of machine learning to virtual screening, focusing on the use of supervised techniques to train statistical learning algorithms to prioritize databases of molecules as active against a partic...
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DOI: https://doi.org/10.2174/138620709788167980
Joost Verbraeken, Matthijs Wolting, Jonathan Katzy, Jeroen Kloppenburg et al. • ACM Computing Surveys
(2020)
The demand for artificial intelligence has grown significantly over the past decade, and this growth has been fueled by advances in machine learning techniques and the ability to leverage hardware acceleration. However, to increase the qual...
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Open Access
DOI: https://doi.org/10.1145/3377454
Xuan V. Nguyen, Devi D. Nelakurti, Engin Dikici, Sema Candemir et al. • Information
(2022)
Background: Distinguishing between the spinal cord and cerebrospinal fluid (CSF) non-invasively on CT is challenging due to their similar mass densities. We hypothesize that patch-based machine learning applied to dual-energy CT can accurat...
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Open Access (DOAJ)
DOI: 10.3390/info13090412