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Academic Articles & Research Papers
Showing 20 of 987 academic articles
Rocio Vargas, Amir Hosein Mosavi, Ramon Ruiz • Preprints.org
(2018)
Deep learning is an emerging area of machine learning (ML) research. It comprises multiple hidden layers of artificial neural networks. The deep learn- ing methodology applies nonlinear transformations and model abstractions of high level i...
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DOI: https://doi.org/10.20944/preprints201810.0218.v1
Shutao Li A, Weiwei Song, Leyuan Fang, Yushi Chen et al. • IEEE Transactions on Geoscience and Remote Sensing
(2019)
Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of hyperspectral data make the accurate classification of such data challenging for traditional machine ...
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Open Access
DOI: https://doi.org/10.1109/tgrs.2019.2907932
Chaoyun Zhang, Paul Patras, Hamed Haddadi • IEEE Communications Surveys & Tutorials
(2019)
The rapid uptake of mobile devices and the rising popularity of mobile applications and services pose unprecedented demands on mobile and wireless networking infrastructure. Upcoming 5G systems are evolving to support exploding mobile traff...
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Open Access
DOI: https://doi.org/10.1109/comst.2019.2904897
Athanasios S. Voulodimos, Nikolaos D. Doulamis, Anastasios D. Doulamis, Eftychios E. Protopapadakis • Computational Intelligence and Neuroscience
(2018)
Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief ...
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DOI: https://doi.org/10.1155/2018/7068349
PMC: 5816885
Travers H. Ching, Daniel Scott Himmelstein, Brett K. Beaulieu‐Jones, Alexandr A. Kalinin et al. • Journal of The Royal Society Interface
(2018)
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and m...
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DOI: https://doi.org/10.1098/rsif.2017.0387
PMC: 5938574
Lei Zhou, Chu Zhang, Fei Liu, Zhengjun Qiu et al. • Comprehensive Reviews in Food Science and Food Safety
(2019)
Deep learning has been proved to be an advanced technology for big data analysis with a large number of successful cases in image processing, speech recognition, object detection, and so on. Recently, it has also been introduced in food sci...
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DOI: https://doi.org/10.1111/1541-4337.12492
Ruud J. G. van Sloun, Regev Cohen, Yonina C. Eldar • Proceedings of the IEEE
(2019)
In this article, we consider deep learning strategies in ultrasound systems, from the front end to advanced applications. Our goal is to provide the reader with a broad understanding of the possible impact of deep learning methodologies on ...
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Open Access
DOI: https://doi.org/10.1109/jproc.2019.2932116
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
Josh Patterson, Gibson Adam (2017)
Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learningespecially deep neural networksmake a real difference in your organization? This han...
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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
Xuedan Du, Yinghao Cai, Shuo Wang, Leijie Zhang • Youth Academic Annual Conference of Chinese Association of Automation (YAC)
(2016)
In recent years, deep learning has achieved great success in many fields, such as computer vision and natural language processing. Compared to traditional machine learning methods, deep learning has a strong learning ability and can make be...
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DOI: https://doi.org/10.1109/yac.2016.7804882
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
Dinggang G. Shen, Guorong Wu A, Heung‐Il Suk • Annual Review of Biomedical Engineering
(2017)
This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical image...
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Open Access
DOI: https://doi.org/10.1146/annurev-bioeng-071516-044442
PMC: 5479722
Justin M. Johnson, Taghi M. Khoshgoftaar • Journal Of Big Data
(2019)
The purpose of this study is to examine existing deep learning techniques for addressing class imbalanced data. Effective classification with imbalanced data is an important area of research, as high class imbalance is naturally inherent in...
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DOI: https://doi.org/10.1186/s40537-019-0192-5
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
Phil Kim • Apress eBooks
(2017)
With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analy...
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DOI: https://doi.org/10.1007/978-1-4842-2845-6
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
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