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Academic Articles & Research Papers
Showing 20 of 95 academic articles
Ming Yan, Jianxi Yang, Cen Chen, Joey Tianyi Zhou et al. • IET Image Processing
(2022)
Abstract Deep neural networks have achieved great success in both computer vision and natural language processing tasks. How to improve the gradient flows is crucial in training very deep neural networks. To address this challenge, a gradie...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/ipr2.12353
Chunxu Qin, Yiran Ma, Huijuan Liang, Zhifan Wang et al. • Modelling
(2026)
The end-winding insulation structure of stator windings in pumped-storage generator units is complex, with pronounced electric field concentration under out-of-phase conditions, making them critical concerns in insulation design and conditi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/modelling7050190
XIONG Zhongmin, ZENG Qi, LU Peng, WANG Zhenhua, ZHENG Zongsheng • Jisuanji gongcheng
(2023)
Logical reasoning is the ability to perceive patterns and connections between visual elements. Endowing computers with human-like reasoning ability is a critical area of research；state-of-the-art deep neural networks have achieved superhuma...
DOAJ
Open Access (DOAJ)
DOI: 10.19678/j.issn.1000-3428.0064591
Vijayamanikandan Vijayarangan, Harshavardhana A. Uranakara, Francisco E. Hernández–Pérez, Hong G. Im • Energy and AI
(2025)
Using information theory, this study provides insights into how the construction of latent space of autoencoder (AE) using deep neural network (DNN) training finds a smooth (non-stiff) low-dimensional manifold in the stiff dynamical system....
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.egyai.2025.100567
Lucas Prado Osco, José Marcato, Ana Paula Marques Ramos, Lúcio André de Castro Jorge et al. • International Journal of Applied Earth Observation and Geoinformation
(2021)
Deep Neural Networks (DNNs) learn representation from data with an impressive capability, and brought important breakthroughs for processing images, time-series, natural language, audio, video, and many others. In the remote sensing field, ...
OPENALEX
cc-by-nc-nd
DOI: https://doi.org/10.1016/j.jag.2021.102456
Nasim Shakouri Mahmoudabadi, Charles V. Camp, Afaq Ahmad • Infrastructures
(2026)
Fiber-reinforced polymer (FRP) composites are widely used to strengthen reinforced concrete (RC) columns due to their high strength, durability, and ease of installation. Accurate prediction of the axial capacity of CFRP-strengthened concre...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/infrastructures11050151
Zetian Zhou, Heqing Zhang, Mehdi Effatparvar • Scientific Reports
(2024)
Abstract Sports image classification is a complex undertaking that necessitates the utilization of precise and robust techniques to differentiate between various sports activities. This study introduces a novel approach that combines the de...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-024-64826-7
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
Changchun Yang, Hengrong Lan, Feng Gao, Fei Gao • Photoacoustics
(2020)
Machine learning has been developed dramatically and witnessed a lot of applications in various fields over the past few years. This boom originated in 2009, when a new model emerged, that is, the deep artificial neural network, which began...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.pacs.2020.100215
PMC: 7779783
• De Gruyter eBooks
(2020)
This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep...
OPENALEX
DOI: https://doi.org/10.1515/9783110670905
JongCheol Pyo, Hongtao Duan, Mayzonee Ligaray, Minjeong Kim et al. • Remote Sensing
(2020)
Hyperspectral image sensing can be used to effectively detect the distribution of harmful cyanobacteria. To accomplish this, physical- and/or model-based simulations have been conducted to perform an atmospheric correction (AC) and an estim...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/rs12071073
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 ...
OPENALEX
DOI: https://doi.org/10.1109/gucon.2018.8675097
Md Zahangir Alom, Tarek M. Taha, Chris Yakopcic, Stefan K.E. Westberg et al. • Electronics
(2019)
In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some ne...
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DOI: https://doi.org/10.3390/electronics8030292
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
Li Deng • APSIPA Transactions on Signal and Information Processing
(2014)
In this invited paper, my overview material on the same topic as presented in the plenary overview session of APSIPA-2011 and the tutorial material presented in the same conference [1] are expanded and updated to include more recent develop...
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DOI: https://doi.org/10.1017/atsip.2013.9
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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cc-by-nc
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
Lisi Zhang, Qiancheng Yu, Beijing Zhou, Yifan Zhang et al. • IEEE Access
(2023)
The efficacy of credit risk assessment models is pivotal to the risk management capacity of financial institutions. Traditional credit risk models often suffer from inadequate predictive accuracy due to overlooked feature combinations and w...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3322429
Swarnendu Ghosh, Nibaran Das, Ishita Das, Ujjwal Maulik • ACM Computing Surveys
(2019)
The machine learning community has been overwhelmed by a plethora of deep learning--based approaches. Many challenging computer vision tasks, such as detection, localization, recognition, and segmentation of objects in an unconstrained envi...
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Open Access
DOI: https://doi.org/10.1145/3329784
Yair Rivenson, Zoltán S. Göröcs, Harun Günaydın, Yibo Zhang et al. • Optica
(2017)
We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field-of-view and depth-of-field. After its training, the only input to this network is an image acquired ...
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Open Access
DOI: https://doi.org/10.1364/optica.4.001437