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Showing 20 of 785 academic articles
LIU Zhaoyang, PAN Bitao • Guangtongxin yanjiu
(2024)
【Objective】Recent research efforts on Routing and Wavelength Assignment (RWA) for all optical networks are focused on Deep Reinforcement Learning (DRL) based algorithms. The DRL based RWA algorithms are mostly rely on the K Shortest Paths (...
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Shin Morishima, Hiroki Matsutani • IEEE Access
(2024)
A computing cluster that interconnects multiple compute nodes is used to accelerate distributed reinforcement learning that uses DQN (Deep Q-Network). In distributed reinforcement learning, actor nodes acquire experiences by interacting wit...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3402835
Mingyu Kim, Jihye Yun, Yongwon Cho, Keewon Shin et al. • Neurospine
(2019)
The artificial neural network (ANN), one of the machine learning (ML) algorithms, inspired by the human brain system, was developed by connecting layers with artificial neurons. However, due to the low computing power and insufficient learn...
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DOI: https://doi.org/10.14245/ns.1938396.198
PMC: 6945006
Xinxin Yu, Yimeng Wang, Long Chen, Weihua Li et al. • Journal of Pharmaceutical Analysis
(2025)
Activity cliffs (ACs) are generally defined as pairs of similar compounds that only differ by a minor structural modification but exhibit a large difference in their binding affinity for a given target. ACs offer crucial insights that aid m...
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Open Access (DOAJ)
DOI: 10.1016/j.jpha.2025.101317
Jiaxi Tang, Yaqin Zhao, Liqi Feng, Wenxuan Zhao • Animals
(2022)
Camera traps are widely used in wildlife research, conservation, and management, and abundant images are acquired every day. Efficient real-time instance segmentation networks can help ecologists label and study wild animals. However, exist...
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Open Access (DOAJ)
DOI: 10.3390/ani12151980
Alexander Craik, Yongtian He, Jose Luis Contreras-Vidal • Journal of Neural Engineering
(2019)
OBJECTIVE: Electroencephalography (EEG) analysis has been an important tool in neuroscience with applications in neuroscience, neural engineering (e.g. Brain-computer interfaces, BCI's), and even commercial applications. Many of the analyti...
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DOI: https://doi.org/10.1088/1741-2552/ab0ab5
Peter L. Bartlett, Andrea Montanari A, Alexander Rakhlin • Acta Numerica
(2021)
The remarkable practical success of deep learning has revealed some major surprises from a theoretical perspective. In particular, simple gradient methods easily find near-optimal solutions to non-convex optimization problems, and despite g...
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DOI: https://doi.org/10.1017/s0962492921000027
Jaya Gupta, Sunil Kumar Pathak, Gireesh Kumar • Journal of Physics Conference Series
(2022)
Abstract Deep Learning is a machine learning area that has recently been used in a variety of industries. Unsupervised, semi-supervised, and supervised-learning are only a few of the strategies that have been developed to accommodate differ...
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DOI: https://doi.org/10.1088/1742-6596/2273/1/012029
Jaesu Han, Sun Yi, Sangseok Yu • Scientific Reports
(2025)
Abstract Many controllers have been developed to control the motors of electric vehicles, but in the case of hydrogen vehicles, more delicate control is required, because power is provided through hybridization with batteries. The use of de...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-97082-4
L. Raghavendar Raju, M. Venkata Krishna Reddy, Sridhar Reddy Surukanti, Gudlanarva Sudhakar et al. • Scientific Reports
(2026)
Abstract Edge–cloud computing has emerged as an important paradigm for modern Internet of Things (IoT) workflow applications, enabling low latency and on-demand resource allocation. In scenarios with heterogeneous deadlines and varying work...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-41330-8
Fen Li, Yu-Ting Si, Jia-Wei Tang, Zeeshan Umar et al. • Computational and Structural Biotechnology Journal
(2024)
WHO classified Helicobacter pylori as a Group I carcinogen for gastric cancer as early as 1994. However, despite the high prevalence of H. pylori infection, only about 3 % of infected individuals eventually develop gastric cancer, with the ...
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Open Access (DOAJ)
DOI: 10.1016/j.csbj.2024.09.008
Marek L. Borowiec, Rebecca B. Dikow, Paul B. Frandsen, Alexander J. McKeeken et al. • Methods in Ecology and Evolution
(2022)
Abstract Deep learning is driving recent advances behind many everyday technologies, including speech and image recognition, natural language processing and autonomous driving. It is also gaining popularity in biology, where it has been use...
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DOI: https://doi.org/10.1111/2041-210x.13901
Jae Joon Hwang, Yun‐Hoa Jung, Bong‐Hae Cho, Min-Suk Heo • Imaging Science in Dentistry
(2019)
PURPOSE: Artificial intelligence (AI), represented by deep learning, can be used for real-life problems and is applied across all sectors of society including medical and dental field. The purpose of this study is to review articles about d...
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DOI: https://doi.org/10.5624/isd.2019.49.1.1
PMC: 6444007
Reza Shokri, Vitaly Shmatikov • ACM SIGSAC Conference on Computer and Communications Security (CCS)
(2015)
Deep learning based on artificial neural networks is a very popular approach to modeling, classifying, and recognizing complex data such as images, speech, and text. The unprecedented accuracy of deep learning methods has turned them into t...
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DOI: https://doi.org/10.1145/2810103.2813687
Ziwei Zhang, Peng Cui, Wenwu Zhu • IEEE Transactions on Knowledge and Data Engineering
(2020)
Deep learning has been shown to be successful in a number of domains, ranging from acoustics, images, to natural language processing. However, applying deep learning to the ubiquitous graph data is non-trivial because of the unique characte...
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Open Access
DOI: https://doi.org/10.1109/tkde.2020.2981333
Sihan Zhou, Gene Thompson • Studies in Second Language Learning and Teaching
(2023)
Listening to academic content in English medium instruction (EMI) classrooms at university can be a demanding task for students who transition from first language (L1) instructed secondary schools. This longitudinal mixed methods study anal...
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Open Access (DOAJ)
DOI: 10.14746/ssllt.38281
Georgios Petmezas, Grigorios-Aris Cheimariotis, Leandros Stefanopoulos, Bruno Rocha et al. • Sensors
(2022)
Respiratory diseases constitute one of the leading causes of death worldwide and directly affect the patient’s quality of life. Early diagnosis and patient monitoring, which conventionally include lung auscultation, are essential for the ef...
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Open Access (DOAJ)
DOI: 10.3390/s22031232
Jianqing Fan, Cong Ma, Yiqiao Zhong • Statistical Science
(2021)
Deep learning has achieved tremendous success in recent years. In simple words, deep learning uses the composition of many nonlinear functions to model the complex dependency between input features and labels. While neural networks have a l...
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Open Access
DOI: https://doi.org/10.1214/20-sts783
PMC: 8300482
Chang Min Hyun, Hwa Pyung Kim, Sung Min Lee, Sungchul Lee et al. • Physics in Medicine and Biology
(2018)
This paper presents a deep learning method for faster magnetic resonance imaging (MRI) by reducing k-space data with sub-Nyquist sampling strategies and provides a rationale for why the proposed approach works well. Uniform subsampling is u...
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DOI: https://doi.org/10.1088/1361-6560/aac71a
Sebastian Macaluso, David Shih • Journal of High Energy Physics
(2018)
Abstract We apply computer vision with deep learning — in the form of a convolutional neural network (CNN) — to build a highly effective boosted top tagger. Previous work (the “DeepTop” tagger of Kasieczka et al) has shown that a CNN-based ...
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Open Access (DOAJ)
DOI: 10.1007/JHEP10(2018)121