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Academic Articles & Research Papers
Showing 20 of 287 academic articles
Shae T. Hart, Jake Kamenetsky, Christopher A. Kitts • IEEE Access
(2023)
Solving the robotic swarm coverage problem for an elliptical area has various applications for exploring novel environments. Solutions for this problem should cover a specified ellipse and seamlessly adapt to changing numbers of robots. Pre...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3244911
Dulani Meedeniya • Chapman & Hall/CRC eBooks
(2023)
This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising....
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public-domain
DOI: https://doi.org/10.1201/9781003390824
P. V. Chandrika, Sandeep Kelkar • Advances in medical diagnosis, treatment, and care (AMDTC) book series
(2024)
This chapter deals with the basic understanding of the deep learning model. It starts with a view of artificial intelligence, machine learning, and deep learning. It also represents how these three concepts are related to each other. The en...
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DOI: https://doi.org/10.4018/979-8-3693-1281-0.ch001
Hun Kim, Jaewoo So • Sensors
(2025)
In a multi-cell network, interference management between adjacent cells is a key factor that determines the performance of the entire cellular network. In particular, in order to control inter-cell interference while providing a high data r...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s25134017
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai et al. • npj Digital Medicine
(2018)
Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variabl...
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DOI: https://doi.org/10.1038/s41746-018-0029-1
PMC: 6550175
Wataru Imai, Masaaki Ikehara • IEEE Access
(2022)
Under severe weather conditions, the quality of the images taken outside is directly affected by floating atmospheric particles. To keep the quality of the images, haze removal methods play a critical role. The most difficult part of haze r...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2022.3204026
Changchun Yang, Hengrong Lan, Feng Gao, Fei Gao • Photoacoustics
(2020)
Machine learning has been developed dramatically and witnessed a lot of applications in various fields over the past few years. This boom originated in 2009, when a new model emerged, that is, the deep artificial neural network, which began...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.pacs.2020.100215
PMC: 7779783
Naledi Lenah Adam, Grzegorz Kowalik, Andrew Tyler, Ronald Mooiweer et al. • Frontiers in Cardiovascular Medicine
(2024)
BackgroundSimultaneous multi-slice (SMS) bSSFP imaging enables stress myocardial perfusion imaging with high spatial resolution and increased spatial coverage. Standard parallel imaging techniques (e.g., TGRAPPA) can be used for image recon...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fcvm.2024.1350345
Sercan Yalçın • Firat University Journal of Experimental and Computational Engineering
(2025)
Tire failures pose significant safety risks, necessitating advanced inspection techniques. This research investigates the application of magnetic sensors and deep learning for detecting defects in steel belts of the tires. It was aim to dev...
DOAJ
Open Access (DOAJ)
DOI: 10.62520/fujece.1527246
Zhen Li, Deqing Zou, Shouhuai Xu, Xinyu Ou et al. • Network and Distributed System Security Symposium
(2018)
The automatic detection of software vulnerabilities is an important research problem.However, existing solutions to this problem rely on human experts to define features and often miss many vulnerabilities (i.e., incurring high false negati...
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Open Access
DOI: https://doi.org/10.14722/ndss.2018.23158
Toke T. Høye, Johanna Ärje, Kim Bjerge, Oskar Liset Pryds Hansen et al. • Proceedings of the National Academy of Sciences
(2021)
ABSTRACT Most animal species on Earth are insects, and recent reports suggest that their abundance is in drastic decline. Although these reports come from a wide range of insect taxa and regions, the evidence to assess the extent of the phe...
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DOI: https://doi.org/10.1073/pnas.2002545117
PMC: 7812775
Xiaojiao Chen, Xiuqing Zhang, Mi Dong, Liansheng Huang et al. • Frontiers in Energy Research
(2021)
The prediction of wind power plays an indispensable role in maintaining the stability of the entire power grid. In this paper, a deep learning approach is proposed for the power prediction of multiple wind turbines. Starting from the time s...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fenrg.2021.723775
Alexander Selvikvåg Lundervold, Arvid Lundervold • Zeitschrift für Medizinische Physik
(2018)
What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started around 2009 when...
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DOI: https://doi.org/10.1016/j.zemedi.2018.11.002
C. E. Ngene, Prabhat Thakur, Ghanshyam Singh • Engineering Reports
(2025)
ABSTRACT This paper proposes a controlled signal technique for visible light non‐orthogonal multiple access (VL‐NOMA) communication in an interference‐controlled environment with intelligent reflecting surfaces (IRS) for beyond 5G (B5G) and...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/eng2.13087
Christopher D. Manning • Computational Linguistics
(2015)
Deep Learning waves have lapped at the shores of computational linguistics for several years now, but 2015 seems like the year when the full force of the tsunami hit the major Natural Language Processing (NLP) conferences. However, some pun...
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Open Access
DOI: https://doi.org/10.1162/coli_a_00239
Aston Zhang, Zachary C. Lipton, Li Mu, Alexander Johannes Smola • arXiv (Cornell University)
(2021)
This open-source book represents our attempt to make deep learning approachable, teaching readers the concepts, the context, and the code. The entire book is drafted in Jupyter notebooks, seamlessly integrating exposition figures, math, and...
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DOI: https://doi.org/10.48550/arxiv.2106.11342
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
Younggill Son, Woongchul Choi • Batteries
(2024)
With the global surge in electric vehicle (EV) deployment, driven by enhanced environmental regulations and efforts to reduce transportation-related greenhouse gas emissions, managing the life cycle of Li-ion batteries becomes more critical...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/batteries10060191
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
Lianlin Li, Hengxin Ruan, Che Liu, Ying Li et al. • Nature Communications
(2019)
Conventional microwave imagers usually require either time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing, making them largely ineffective for complex in-situ sensing and monitoring. Here, we e...
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DOI: https://doi.org/10.1038/s41467-019-09103-2
PMC: 6403242