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Showing 20 of 777 academic articles
ZHANG Lei, LI Yuewen, SHI Yi • Guangtongxin yanjiu
(2026)
Due to the dynamic monitoring capability, Distributed Acoustic Sensing (DAS) has been widely deployed in various industrial scenarios. Deep learning greatly boosts the event detection accuracy of fiber sensing systems. Nevertheless, practic...
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Open Access (DOAJ)
Chao Zuo, Jiaming Qian, Shijie Feng, Wei Yin et al. • Light Science & Applications
(2022)
With the advances in scientific foundations and technological implementations, optical metrology has become versatile problem-solving backbones in manufacturing, fundamental research, and engineering applications, such as quality control, n...
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DOI: https://doi.org/10.1038/s41377-022-00714-x
PMC: 8866517
Pramila P. Shinde, Seema Shah • International Conference on Computing Communication Control and automation
(2018)
Machine learning is one of the fields in the modern computing world. A plenty of research has been undertaken to make machines intelligent. Learning is a natural human behavior which has been made an essential aspect of the machines as well...
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DOI: https://doi.org/10.1109/iccubea.2018.8697857
Hongming Chen, Ola Engkvist, Yinhai Wang, Marcus Olivecrona et al. • Drug Discovery Today
(2018)
Over the past decade, deep learning has achieved remarkable success in various artificial intelligence research areas. Evolved from the previous research on artificial neural networks, this technology has shown superior performance to other...
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DOI: https://doi.org/10.1016/j.drudis.2018.01.039
Polina Mamoshina, Armando S. Vieira, Eugene Lane, Alex A. Zhavoronkov • Molecular Pharmaceutics
(2016)
Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this ...
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DOI: https://doi.org/10.1021/acs.molpharmaceut.5b00982
Siwei Yu, Jianwei Ma, Wenlong Wang • Geophysics
(2019)
ABSTRACT Compared with traditional seismic noise attenuation algorithms that depend on signal models and their corresponding prior assumptions, removing noise with a deep neural network is trained based on a large training set in which the ...
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Open Access
DOI: https://doi.org/10.1190/geo2018-0668.1
Ko-Tsung Hsu, Steven Guan, Parag V. Chitnis • Photoacoustics
(2023)
Iterative reconstruction has demonstrated superior performance in medical imaging under compressed, sparse, and limited-view sensing scenarios. However, iterative reconstruction algorithms are slow to converge and rely heavily on hand-craft...
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Open Access (DOAJ)
DOI: 10.1016/j.pacs.2023.100452
Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu • Journal of Computational Chemistry
(2017)
The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning,...
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Open Access
DOI: https://doi.org/10.1002/jcc.24764
Terrence J. Sejnowski A B • The MIT Press eBooks
(2018)
How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy.The deep learning revolution has brought us driverless cars, the greatly improved...
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DOI: https://doi.org/10.7551/mitpress/11474.001.0001
Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn • BMC Medical Imaging
(2025)
Abstract Background and purpose Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI) is tedious and time-consuming for radiologists that could be optimized with deep learning (DL). Previous studies assessed several ...
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Open Access (DOAJ)
DOI: 10.1186/s12880-025-01643-y
Hao Xing, Guigang Zhang, Shang Ma • International Journal of Semantic Computing
(2016)
Deep learning is a branch of machine learning that tries to model high-level abstractions of data using multiple layers of neurons consisting of complex structures or non-liner transformations. With the increase of the amount of data and th...
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DOI: https://doi.org/10.1142/s1793351x16500045
John D. Kelleher • The MIT Press eBooks
(2019)
An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vi...
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DOI: https://doi.org/10.7551/mitpress/11171.001.0001
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
Ian Goodfellow, Yoshua Bengio, Aaron C. Courville • The MIT Press eBooks
(2016)
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human c...
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DOI: https://doi.org/10.1016/b978-0-12-804291-5.00010-6
Kamel Arafet, Rafael Berlanga • Algorithms
(2021)
The generation of electricity through renewable energy sources increases every day, with solar energy being one of the fastest-growing. The emergence of information technologies such as Digital Twins (DT) in the field of the Internet of Thi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/a14050156
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
Luigi Capogrosso, Federico Cunico, Dong Seon Cheng, Franco Fummi et al. • IEEE Access
(2024)
The emergence of Tiny Machine Learning (TinyML) has positively revolutionized the field of Artificial Intelligence by promoting the joint design of resource-constrained IoT hardware devices and their learning-based software architectures. T...
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DOI: https://doi.org/10.1109/access.2024.3365349
Ahmed E. Radwan, David A. Wood, Ahmed A. Radwan • Journal of Rock Mechanics and Geotechnical Engineering
(2022)
Pore pressure is an essential parameter for establishing reservoir conditions, geological interpretation and drilling programs. Pore pressure prediction depends on information from various geophysical logs, seismic, and direct down-hole pre...
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Open Access (DOAJ)
DOI: 10.1016/j.jrmge.2022.01.012
Supriya D. Mehta, Dan Zhao, Stefan J. Green, Walter Agingu et al. • Frontiers in Cellular and Infection Microbiology
(2020)
Background: We determined the predictive accuracy of penile bacteria for incident BV in female sex partners. In this prospective cohort, we enrolled Kenyan men aged 18–35 and their female sex partners aged 16 and older. We assessed BV at ba...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fcimb.2020.00433
Ognjen Radišić-Aberger, Peter Burggräf, Fabian Steinberg, Alexander Becher et al. • Supply Chain Analytics
(2024)
By applying machine learning algorithms, predictive business process monitoring (PBPM) techniques provide an opportunity to counteract undesired outcomes of processes. An especially complex variation of business processes is the engineering...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.sca.2024.100087