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Showing 20 of 1,128 academic articles
Haohan Wang, Bhiksha Raj • arXiv (Cornell University)
(2017)
This paper is a review of the evolutionary history of deep learning models. It covers from the genesis of neural networks when associationism modeling of the brain is studied, to the models that dominate the last decade of research in deep ...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1702.07800
Bethany Lusch, J. Nathan Kutz, Steven L. Brunton • Nature Communications
(2018)
Identifying coordinate transformations that make strongly nonlinear dynamics approximately linear has the potential to enable nonlinear prediction, estimation, and control using linear theory. The Koopman operator is a leading data-driven e...
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DOI: https://doi.org/10.1038/s41467-018-07210-0
PMC: 6251871
François Chollet, JJ Allaire (2018)
Introduces deep learning systems using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples...
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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
Xiao Xiang Zhu, Devis Tuia, Lichao Mou, Gui-Song Xia et al. • IEEE Geoscience and Remote Sensing Magazine
(2017)
Central to the looming paradigm shift toward data-intensive science, machine-learning techniques are becoming increasingly important. In particular, deep learning has proven to be both a major breakthrough and an extremely powerful tool in ...
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Open Access
DOI: https://doi.org/10.1109/mgrs.2017.2762307
Fuyong Xing, Yuanpu Xie, Hai Su, Fujun Liu et al. • IEEE Transactions on Neural Networks and Learning Systems
(2017)
Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerg...
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DOI: https://doi.org/10.1109/tnnls.2017.2766168
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 ...
DOAJ
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
Senzhang Wang, Jiannong Cao, Philip S. Yu • IEEE Transactions on Knowledge and Data Engineering
(2020)
With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly available nowadays. Mining valuable knowledge from spatio-temp...
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Open Access
DOI: https://doi.org/10.1109/tkde.2020.3025580
D. Guest, Kyle Stuart Cranmer, Daniel Whiteson • Annual Review of Nuclear and Particle Science
(2018)
Machine learning has played an important role in the analysis of high-energy physics data for decades. The emergence of deep learning in 2012 allowed for machine learning tools which could adeptly handle higher-dimensional and more complex ...
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Open Access
DOI: https://doi.org/10.1146/annurev-nucl-101917-021019
Sara Sheehan, Yun S. Song • PLoS Computational Biology
(2016)
Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep...
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DOI: https://doi.org/10.1371/journal.pcbi.1004845
PMC: 4809617
Shuochao Yao, Yiran Zhao, Aston Zhang, Shaohan Hu et al. • Computer
(2018)
How can the advantages of deep learning be brought to the emerging world of embedded IoT devices? The authors discuss several core challenges in embedded and mobile deep learning, as well as recent solutions demonstrating the feasibility of...
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DOI: https://doi.org/10.1109/mc.2018.2381131
Yanhui Xi, Weijie Zhang, Feng Zhou, Xin Tang et al. • Energy Reports
(2023)
Accurate fault detection and classification help to analyze fault causes and quickly restore faulty phases. Deep learning can automatically extract fault features and identify fault types from the original three-phase voltage and current si...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.egyr.2022.12.043
Nitin Kumar Chauhan, Krishna Pal Singh • International Conference on Computing, Power and Communication Technologies (GUCON)
(2018)
In now days, deep learning has become a prominent and emerging research area in computer vision applications. Deep learning permits the multiple layers models for computation to learn representations of data by processing in their original ...
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DOI: https://doi.org/10.1109/gucon.2018.8675097
Saifullahi Aminu Bello, Shangshu Yu, Cheng Wang, Jibril Muhammad Adam et al. • Remote Sensing
(2020)
A point cloud is a set of points defined in a 3D metric space. Point clouds have become one of the most significant data formats for 3D representation and are gaining increased popularity as a result of the increased availability of acquisi...
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DOI: https://doi.org/10.3390/rs12111729
Wan Zhu, Longxiang Xie, Jianye Han, Xiangqian Guo • Cancers
(2020)
Deep learning has been applied to many areas in health care, including imaging diagnosis, digital pathology, prediction of hospital admission, drug design, classification of cancer and stromal cells, doctor assistance, etc. Cancer prognosis...
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DOI: https://doi.org/10.3390/cancers12030603
PMC: 7139576
SUN Xuechao, ZHANG Youyuan, ZHU Jinxiang, WANG Ping et al. • Renmin Zhujiang
(2025)
Broken wire electromagnetic detection technology for prestressed concrete cylinder pipes (PCCPs) is an important technical means to maintain the safety of PCCP engineering. Although electromagnetic detection technology has a high detection ...
DOAJ
Open Access (DOAJ)
Xiaozheng Li, Huazhen Wang, Huixin He, Jixiang Du et al. • BMC Bioinformatics
(2019)
Abstract Background Benefiting from big data, powerful computation and new algorithmic techniques, we have been witnessing the renaissance of deep learning, particularly the combination of natural language processing (NLP) and deep neural n...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12859-019-2617-8
June‐Goo Lee, Sanghoon Jun, Young-Won Cho, Hyunna Lee et al. • Korean Journal of Radiology
(2017)
The artificial neural network (ANN)-a machine learning technique inspired by the human neuronal synapse system-was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishin...
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DOI: https://doi.org/10.3348/kjr.2017.18.4.570
PMC: 5447633
Yanming Yang, Xin Xia, David Lo, John Grundy • ACM Computing Surveys
(2021)
In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)” and an improved model training method to break the bottleneck of neural network development. More recently, the introduction of AlphaGo in 2016 demonstr...
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Open Access
DOI: https://doi.org/10.1145/3505243