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Academic Articles & Research Papers
Showing 20 of 547 academic articles
Hideyuki Ogura, Masaaki Ikehara • IEEE Access
(2025)
Image colorization is a fundamental task in computer vision that aims to predict the missing color channels from grayscale images. In recent years, fully automatic approaches based on deep learning have become the dominant paradigm. However...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3646876
Jiasi Chen, Xukan Ran • Proceedings of the IEEE
(2019)
Deep learning is currently widely used in a variety of applications, including computer vision and natural language processing. End devices, such as smartphones and Internet-of-Things sensors, are generating data that need to be analyzed in...
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DOI: https://doi.org/10.1109/jproc.2019.2921977
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
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
Shuai Zhang, Lina Yao, Aixin Sun, Yi Tay • ACM Computing Surveys
(2019)
With the growing volume of online information, recommender systems have been an effective strategy to overcome information overload. The utility of recommender systems cannot be overstated, given their widespread adoption in many web applic...
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Open Access
DOI: https://doi.org/10.1145/3285029
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
Kalaivani Sundararajan, Damon L. Woodard • ACM Computing Surveys
(2018)
In the recent past, deep learning methods have demonstrated remarkable success for supervised learning tasks in multiple domains including computer vision, natural language processing, and speech processing. In this article, we investigate ...
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DOI: https://doi.org/10.1145/3190618
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
Greg Zaharchuk, Enhao Gong, Max Wintermark, Daniel L. Rubin et al. • American Journal of Neuroradiology
(2018)
Deep learning is a form of machine learning using a convolutional neural network architecture that shows tremendous promise for imaging applications. It is increasingly being adapted from its original demonstration in computer vision applic...
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DOI: https://doi.org/10.3174/ajnr.a5543
PMC: 7410723
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
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
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
Jeremy M. Watt, Reza Borhani, Aggelos K. Katsaggelos • Cambridge University Press eBooks
(2020)
With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuiti...
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DOI: https://doi.org/10.1017/9781108690935
Subrata Chakraborty, Biswajeet Pradhan • Sensors
(2024)
Machine learning (ML) models have experienced remarkable growth in their application for multimodal data analysis over the past decade [...]...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s24092874
Masoud Mahdianpari, Bahram Salehi, Mohammad Rezaee, Fariba Mohammadimanesh et al. • Remote Sensing
(2018)
Despite recent advances of deep Convolutional Neural Networks (CNNs) in various computer vision tasks, their potential for classification of multispectral remote sensing images has not been thoroughly explored. In particular, the applicatio...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs10071119
Nishant Shukla • CERN Document Server (European Organization for Nuclear Research)
(2018)
Summary Machine Learning with Tensor Flow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding Tensor Flow with Python. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub forma...
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Laura ONAC • Studia Universitatis Babes-Bolyai: Series Informatica
(2019)
Plant recognition represents a challenging computer vision problem due to the great variations of shape and texture among plant organs, within the same species. This paper proposes a light-weight, but reasonably deep Convolutional Neural Ne...
DOAJ
Open Access (DOAJ)
DOI: 10.24193/subbi.2019.1.01
Ziyi Yin, Guowei Huang, Rui Zhao, Sen Wang et al. • Financial Innovation
(2024)
Abstract Crowdfunding has become important in increasing financial support for the development of green technologies. Self-disclosed information significantly affects supporters’ decisions and is important for the success of green project f...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s40854-024-00666-8
Anzar Abbas, Vijay Yadav, Emma Smith, Elizabeth Ramjas et al. • Digital Biomarkers
(2021)
Introduction: Motor abnormalities have been shown to be a distinct component of schizophrenia symptomatology. However, objective and scalable methods for assessment of motor functioning in schizophrenia are lacking. Advancements in machine ...
DOAJ
Open Access (DOAJ)
DOI: 10.1159/000512383
Kevin P. Murphy (2012)
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict fu...
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