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Showing 20 of 4,934 academic articles
Lili Li, Shujuan Zhang, Bin Wang • IEEE Access
(2021)
Deep learning is a branch of artificial intelligence. In recent years, with the advantages of automatic learning and feature extraction, it has been widely concerned by academic and industrial circles. It has been widely used in image and v...
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DOI: https://doi.org/10.1109/access.2021.3069646
Xinhang Zhang, Zhenhua Ma, Yaru Zhang, Huiying Ru • IEEE Access
(2025)
The recognition of oracle bone script is of significant importance for understanding the evolution of Chinese characters, their morphological features, and semantic changes. However, traditional methods and some deep learning models have li...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3536553
Thomas Hu, Mayar Allam, Shuangyi Cai, Walter Henderson et al. • Nature Communications
(2023)
Abstract Metabolic reprogramming in cancer and immune cells occurs to support their increasing energy needs in biological tissues. Here we propose Single Cell Spatially resolved Metabolic (scSpaMet) framework for joint protein-metabolite pr...
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Open Access (DOAJ)
DOI: 10.1038/s41467-023-43917-5
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
Chao-Kai Wen, Wan-Ting Shih, Shi Jin • IEEE Wireless Communications Letters
(2018)
In frequency division duplex mode, the downlink channel state information (CSI) should be sent to the base station through feedback links so that the potential gains of a massive multiple-input multiple-output can be exhibited. However, suc...
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Open Access
DOI: https://doi.org/10.1109/lwc.2018.2818160
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
Boris Pyakillya, Н. Я. Казаченко, N Mikhailovsky • Journal of Physics Conference Series
(2017)
The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG d...
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DOI: https://doi.org/10.1088/1742-6596/913/1/012004
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
Liyue Wu, Qinchuan Zhan, Yanjun Li • Humanities & Social Sciences Communications
(2026)
Abstract This study applies a multimodal deep learning approach to examine tourist engagement with traditional architectural heritage. The Gao Family Compound in Xi’an serves as a representative case. Social-media texts and images from Weib...
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Open Access (DOAJ)
DOI: 10.1057/s41599-026-07879-5
Yasha Ektefaie, William Yuan, Deborah A. Dillon, Nancy U. Lin et al. • npj Breast Cancer
(2021)
Abstract Histopathologic evaluation of biopsy slides is a critical step in diagnosing and subtyping breast cancers. However, the connections between histology and multi-omics status have never been systematically explored or interpreted. We...
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Open Access (DOAJ)
DOI: 10.1038/s41523-021-00357-y
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