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Academic Articles & Research Papers
Showing 20 of 1,100 academic articles
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
Zhong‐Qiu Zhao, Peng Zheng, Shou-Tao Xu, Xindong Wu • IEEE Transactions on Neural Networks and Learning Systems
(2019)
Due to object detection's close relationship with video analysis and image understanding, it has attracted much research attention in recent years. Traditional object detection methods are built on handcrafted features and shallow trainable...
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Open Access
DOI: https://doi.org/10.1109/tnnls.2018.2876865
Fangzhou Liu, Yang Zhao, Jiqiao Chen, Ting Luo • EAI Endorsed Transactions on Energy Web
(2026)
Power distribution network fault handling imposes stringent requirements on both response timeliness and decision reliability. The high penetration of distributed renewable generation, the widespread deployment of power-electronic devices, ...
DOAJ
Open Access (DOAJ)
DOI: 10.4108/ew.13683
Lei Zhang, Shuai Wang, Bing Liu • Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
(2018)
Deep learning has emerged as a powerful machine learning technique that learns multiple layers of representations or features of the data and produces state‐of‐the‐art prediction results. Along with the success of deep learning in many appl...
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Open Access
DOI: https://doi.org/10.1002/widm.1253
Neil Thompson, Kristjan H. Greenewald, Keeheon Lee, Gabriel F. Manso (2023)
Deep learning's recent history has been one of achievement: from triumphing over humans in the game of Go to world-leading performance in image classification, voice recognition, translation, and other tasks.But this progress has come with ...
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DOI: https://doi.org/10.21428/bf6fb269.1f033948
Gabriel Chartrand, Phillip M. Cheng, Eugene Vorontsov, Michal Drozdzal et al. • Radiographics
(2017)
Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods prod...
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DOI: https://doi.org/10.1148/rg.2017170077
Lisha Nie, Siyi Li, Bing Wu, Yuhui Xiong et al. • iRADIOLOGY
(2024)
Abstract The development of 7‐Tesla (7T) magnetic resonance imaging systems has opened new avenues for exploring the advantages of diffusion imaging at higher field strengths, especially in neuroscience research. This review investigates wh...
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Open Access (DOAJ)
DOI: 10.1002/ird3.92
Daniele Ravì, Charence Wong, Fani Deligianni, Melissa Berthelot et al. • IEEE Journal of Biomedical and Health Informatics
(2016)
With a massive influx of multimodality data, the role of data analytics in health informatics has grown rapidly in the last decade. This has also prompted increasing interests in the generation of analytical, data driven models based on mac...
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DOI: https://doi.org/10.1109/jbhi.2016.2636665
Wenqiang Liu, Li Yan, Ningning Ma, Gaozhou Wang et al. • Applied Sciences
(2024)
With the rapid development of deep learning, researchers are actively exploring its applications in the field of industrial anomaly detection. Deep learning methods differ significantly from traditional mathematical modeling approaches, eli...
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Open Access (DOAJ)
DOI: 10.3390/app14020774
Adam C. Mater, Michelle L. Coote • Journal of Chemical Information and Modeling
(2019)
Machine learning enables computers to address problems by learning from data. Deep learning is a type of machine learning that uses a hierarchical recombination of features to extract pertinent information and then learn the patterns repres...
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DOI: https://doi.org/10.1021/acs.jcim.9b00266
S. Mostafa Mousavi, Gregory C. Beroza • Science
(2022)
Seismic waves from earthquakes and other sources are used to infer the structure and properties of Earth's interior. The availability of large-scale seismic datasets and the suitability of deep-learning techniques for seismic data processin...
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DOI: https://doi.org/10.1126/science.abm4470
Li Deng, Dong Yu • Foundations and Trends® in Signal Processing
(2014)
This monograph provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks. The application areas are chosen with the following three criteria in mind: (1) expertise...
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Open Access
DOI: https://doi.org/10.1561/2000000039
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
Max Mowbray, Thomas Savage, Chufan Wu, Ziqi Song et al. • Biochemical Engineering Journal
(2021)
The field of machine learning is comprised of techniques, which have proven powerful approaches to knowledge discovery and construction of ‘digital twins’ in the highly dimensional, nonlinear and stochastic domains common to biochemical eng...
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DOI: https://doi.org/10.1016/j.bej.2021.108054
William W. Hsieh • Cambridge University Press eBooks
(2009)
Machine learning methods originated from artificial intelligence and are now used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of machine learning methods and th...
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DOI: https://doi.org/10.1017/cbo9780511627217
Sun Ping • Materials Research Express
(2026)
Polymer solar cells (PSCs) rely on labor-intensive trial-and-error experiments to optimize power conversion efficiency (PCE), due to complex coupling of molecular electronic properties, blend morphology and fabrication parameters. This work...
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Open Access (DOAJ)
DOI: 10.1088/2053-1591/aeaacc
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