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Showing 20 of 777 academic articles
Asmaa Hani Halbouni, Teddy Surya Gunawan, Mohamed Hadi Habaebi, Murad Halbouni et al. • IEEE Access
(2022)
The rapid evolution and growth of the internet through the last decades led to more concern about cyber-attacks that are continuously increasing and changing. As a result, an effective intrusion detection system was required to protect data...
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DOI: https://doi.org/10.1109/access.2022.3151248
DeLiang Wang, Jitong Chen • IEEE/ACM Transactions on Audio Speech and Language Processing
(2018)
Speech separation is the task of separating target speech from background interference. Traditionally, speech separation is studied as a signal processing problem. A more recent approach formulates speech separation as a supervised learning...
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Open Access
DOI: https://doi.org/10.1109/taslp.2018.2842159
PMC: 6586438
Zihao Zhang, Stefan Zohren, Stephen Roberts • The Journal of Financial Data Science
(2020)
In this article, the authors adopt deep learning models to directly optimize the portfolio Sharpe ratio. The framework they present circumvents the requirements for forecasting expected returns and allows them to directly optimize portfolio...
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Open Access
DOI: https://doi.org/10.3905/jfds.2020.1.042
Sidrah Liaqat, Kia Dashtipour, Adnan Zahid, Khaled Assaleh et al. • Information
(2020)
The atrial fibrillation (AF) is one of the most well-known cardiac arrhythmias in clinical practice, with a prevalence of 1–2% in the community, which can increase the risk of stroke and myocardial infarction. The detection of AF electrocar...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/info11120549
James Bergstra, Frédéric Bastien, Olivier Breuleux, Pascal Lamblin et al. (2012)
In this paper, we present Theano1, a framework in the Python programming language for defining, optimizing and evaluating expressions involving high-level operations on ten-sors. Theano offers most of NumPy’s functionality, but adds automat...
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• De Gruyter eBooks
(2020)
This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep...
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DOI: https://doi.org/10.1515/9783110670905
Navin Kumar Manaswi • Apress eBooks
(2018)
This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with Applications Using Python covers topics such ...
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DOI: https://doi.org/10.1007/978-1-4842-3516-4
WANG Ziyi, GUO Shaoyong, CHEN Jiewei, XIAO Yitao et al. • Tongxin xuebao
(2026)
With the rapid growth of AI, data-center energy consumption continues to increase. To balance computing service requirements and renewable-energy fluctuations, a grid carbon-intensity-aware power–computing coordinated scheduling method was ...
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Open Access (DOAJ)
Iraj Abedi, Mahsa Vali, Bentolhoda Otroshi, Maryam Zamanian et al. • BMC Research Notes
(2024)
Abstract Introduction Computed tomography (CT) was a widely used diagnostic technique for COVID-19 during the pandemic. High-Resolution Computed Tomography (HRCT), is a type of computed tomography that enhances image resolution through the ...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s13104-024-06693-z
Dimitrios Georgiou, Sotiris Kotsiantis, Fotini Sereti • Mathematics
(2026)
Topological data analysis (TDA) has evolved into a flexible and robust paradigm for obtaining qualitative, geometry-inspired insights from high-dimensional, noisy, and complex data. Grounded in algebraic topology, geometry, statistics, and ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/math14122205
Thomas Serre • Annual Review of Vision Science
(2019)
Artificial vision has often been described as one of the key remaining challenges to be solved before machines can act intelligently. Recent developments in a branch of machine learning known as deep learning have catalyzed impressive gains...
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DOI: https://doi.org/10.1146/annurev-vision-091718-014951
Junjie Ji, Yongzhang Zhou, Qiuming Cheng, Shoujun Jiang et al. • Land
(2023)
Selecting samples with non-landslide attributes significantly impacts the deep-learning modeling of landslide susceptibility mapping. This study presents a method of information value analysis in order to optimize the selection of negative ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/land12061125
Priya Mathur, Dheeraj Kumar, Farhan Sheth, Hammad Shaikh et al. • Scientific Reports
(2025)
Abstract Accurately predicting the specific heat capacity of nanofluids is critical for optimizing their performance in engineering and industrial applications. This study explores twelve machine learning and deep learning models using conv...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-28268-z
Da Yuan, Dong Huang, Yu Lei, Minhao Wang et al. • Applied Sciences
(2026)
The penetration rate (PR) is a critical indicator affecting the safety and cost of shield tunnel construction. However, due to the complexity of geological conditions and the nonlinear nature of tunneling parameters, traditional prediction ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app16115549
Fatima Rauf, Muhammad Attique Khan, Ali Kashif Bashir, Kiran Jabeen et al. • Frontiers in Medicine
(2023)
Despite a worldwide decline in maternal mortality over the past two decades, a significant gap persists between low- and high-income countries, with 94% of maternal mortality concentrated in low and middle-income nations. Ultrasound serves ...
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Open Access (DOAJ)
DOI: 10.3389/fmed.2023.1330218
Ammar Mohammed, Rania Kora • Journal of King Saud University - Computer and Information Sciences
(2023)
In machine learning, two approaches outperform traditional algorithms: ensemble learning and deep learning. The former refers to methods that integrate multiple base models in the same framework to obtain a stronger model that outperforms t...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.jksuci.2023.01.014
Hao Wang, Xuan Wang, Yusheng Du, You Wang et al. • European Journal of Radiology Open
(2025)
Objectives: This study aimed to develop a predictive model for lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) patients by deep learning radiomic (DLRad) and clinical features. Methods: This study included 271 thyroid lobes...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.ejro.2025.100639
Li Deng • APSIPA Transactions on Signal and Information Processing
(2014)
In this invited paper, my overview material on the same topic as presented in the plenary overview session of APSIPA-2011 and the tutorial material presented in the same conference [1] are expanded and updated to include more recent develop...
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DOI: https://doi.org/10.1017/atsip.2013.9
Chayakrit Krittanawong, Kipp W. Johnson, Robert S. Rosenson, Zhen Wang et al. • European Heart Journal
(2019)
Deep learning (DL) is a branch of machine learning (ML) showing increasing promise in medicine, to assist in data classification, novel disease phenotyping and complex decision making. Deep learning is a form of ML typically implemented via...
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Open Access
DOI: https://doi.org/10.1093/eurheartj/ehz056
PMC: 6600129
Nir Shlezinger, Yonina C. Eldar, Stephen Boyd • IEEE Access
(2022)
Decision making algorithms are used in a multitude of different applications. Conventional approaches for designing decision algorithms employ principled and simplified modelling, based on which one can determine decisions via tractable opt...
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DOI: https://doi.org/10.1109/access.2022.3218802