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Showing 20 of 1,964 academic articles
Zhihao Chen, Jie Gao, Weikai Wang, Zheng Yan • Environmental Research Letters
(2021)
The troposphere is one of the atmospheric layers where most weather phenomena occur. Temperature variations in the troposphere, especially at 500 hPa, a typical level of the middle troposphere, are significant indicators of future weather c...
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Open Access (DOAJ)
DOI: 10.1088/1748-9326/abfde9
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 ...
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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...
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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
Chayakrit Krittanawong, Kipp W. Johnson, Robert S. Rosenson, Zhen Wang et al. • European Heart Journal
(2019)
Deep learning (DL) is a branch of machine learning (ML) showing increasing promise in medicine, to assist in data classification, novel disease phenotyping and complex decision making. Deep learning is a form of ML typically implemented via...
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Open Access
DOI: https://doi.org/10.1093/eurheartj/ehz056
PMC: 6600129
Risheng Wang, Tao Lei, Ruixia Cui, Bingtao Zhang et al. • IET Image Processing
(2022)
Abstract Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field. A comprehensive thematic survey on medical image segmentation us...
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DOI: https://doi.org/10.1049/ipr2.12419
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
He Li, Kaoru Ota, Mianxiong Dong • IEEE Network
(2018)
Deep learning is a promising approach for extracting accurate information from raw sensor data from IoT devices deployed in complex environments. Because of its multilayer structure, deep learning is also appropriate for the edge computing ...
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Open Access
DOI: https://doi.org/10.1109/mnet.2018.1700202
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
Daniel W. Otter, Julian Richard Medina, Jugal Kumar Kalita • IEEE Transactions on Neural Networks and Learning Systems
(2020)
Over the last several years, the field of natural language processing has been propelled forward by an explosion in the use of deep learning models. This article provides a brief introduction to the field and a quick overview of deep learni...
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Open Access
DOI: https://doi.org/10.1109/tnnls.2020.2979670
Abderrazak Khediri, Ayoub Yahiaoui, Mohamed Ridda Laouar, Yacine Belhocine • Acta Informatica Pragensia
(2024)
Blackout events in smart grids can have significant impacts on individuals, communities and businesses, as they can disrupt the power supply and cause damage to the grid. In this paper, a new proactive approach to an early warning system fo...
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Open Access (DOAJ)
DOI: 10.18267/j.aip.246
Genwei Ma, Yining Zhu, Xing Zhao • IEEE Access
(2020)
The x-ray computed tomography (CT) is essential for medical diagnosis and industrial nondestructive testing. The aim of CT is to recover or reconstruct image from projection data. However, in particular, the reconstructed image usually suff...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.3039638
Fudong Xue, Lin Yuan, Wenting He, Zuo’ang Xiang et al. • Nature Communications
(2026)
Abstract Computational super-resolution (SR) methods enable nanoscale imaging from single-frame wide-field or spinning-disk confocal images without hardware modifications, yet face limitations: statistical restoration suffers from noise and...
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Open Access (DOAJ)
DOI: 10.1038/s41467-026-70791-8
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...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3322429
Konstantinos Keremis, Eleni Vrochidou, George A. Papakostas • Journal of Imaging
(2025)
The ability of deep learning models to maintain consistent performance under image transformations-termed invariances, is critical for reliable deployment across diverse computer vision applications. This study presents a comprehensive empi...
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Open Access (DOAJ)
DOI: 10.3390/jimaging11090322
Jishi Zheng, Junhui Li, Zhigang Ding, Linghua Kong et al. • Connection Science
(2023)
To prevent products with missing character information from reaching the market, manufacturers need an automatic character recognition method. One of the key problems of this recognition method is to recognise text under complex package pat...
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Open Access (DOAJ)
DOI: 10.1080/09540091.2023.2202363
Guangyu Zhu, Xueqi Luo, Tingting Yang, Li Cai et al. • Frontiers in Physiology
(2022)
The manual identification and segmentation of intracranial aneurysms (IAs) involved in the 3D reconstruction procedure are labor-intensive and prone to human errors. To meet the demands for routine clinical management and large cohort studi...
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Open Access (DOAJ)
DOI: 10.3389/fphys.2022.1084202
Le Yang, Dongmei Jiang, Hichem Sahli • IEEE Access
(2020)
Depression disorder has become one of the major psychological diseases endangering human health. Researcher in the affective computing community is supporting the development of reliable depression severity estimation system, from multiple ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.2970496
Zhen Li, Deqing Zou, Shouhuai Xu, Xinyu Ou et al. • Network and Distributed System Security Symposium
(2018)
The automatic detection of software vulnerabilities is an important research problem.However, existing solutions to this problem rely on human experts to define features and often miss many vulnerabilities (i.e., incurring high false negati...
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Open Access
DOI: https://doi.org/10.14722/ndss.2018.23158
Andre Esteva, Katherine Chou, Serena Y. Yeung, Nikhil Naik et al. • npj Digital Medicine
(2021)
A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the potential for many fields-including medicine-to benefit from the insights that AI techniques can extract from data. Here we survey recent progress in th...
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DOI: https://doi.org/10.1038/s41746-020-00376-2
PMC: 7794558