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Academic Articles & Research Papers
Showing 20 of 122 academic articles
Heather Symecko, Robert Schnoll, Rinad S. Beidas, Justin E. Bekelman et al. • Implementation Science
(2023)
Abstract Background Germline genetic testing is recommended by the National Comprehensive Cancer Network (NCCN) for individuals including, but not limited to, those with a personal history of ovarian cancer, young-onset (...
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Open Access (DOAJ)
DOI: 10.1186/s13012-023-01308-w
Michael Safo Oduro, Eniola Fasola, Prince Peprah, Isaac Yeboah Addo • BMC Public Health
(2025)
Abstract Background There is a dearth of studies focused on the impact of self-rated health on life satisfaction among large-bodied adolescents, as well as the moderating role of physical activity in this relationship. Large-bodied adolesce...
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Open Access (DOAJ)
DOI: 10.1186/s12889-025-23626-y
Michael Doube • Royal Society Open Science
(2021)
Sequential region labelling, also known as connected components labelling, is a standard image segmentation problem that joins contiguous foreground pixels into blobs. Despite its long development history and widespread use across diverse d...
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Open Access (DOAJ)
DOI: 10.1098/rsos.201784
Fangfang Huang, Ting Shen, Xin Hai, Huiqing Xiu et al. • Heliyon
(2022)
Purpose: To investigate the clinical features and risk factors for methicillin-resistant Staphylococcus aureus (MRSA) pneumonia (MP) with secondary MRSA bloodstream infections (MRSA-BSI) (termed MP-BSI) compared with MP alone and to study t...
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Open Access (DOAJ)
DOI: 10.1016/j.heliyon.2022.e11978
Aamir Shahzad, Malrey Lee, Neal Naixue Xiong, Gisung Jeong et al. • Sensors
(2016)
In Industrial systems, Supervisory control and data acquisition (SCADA) system, the pseudo-transport layer of the distributed network protocol (DNP3) performs the functions of the transport layer and network layer of the open systems interc...
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Open Access (DOAJ)
DOI: 10.3390/s16030322
Wazir Ali, Jay Kumar, Zenglin Xu, Rajesh Kumar et al. • Applied Sciences
(2021)
Named entity recognition (NER) is a fundamental task in many natural language processing (NLP) applications, such as text summarization and semantic information retrieval. Recently, deep neural networks (NNs) with the attention mechanism yi...
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Open Access (DOAJ)
DOI: 10.3390/app11199038
Sebastian Ruder • Arrow@dit (Dublin Institute of Technology)
(2019)
The current generation of neural network-based natural language processing models excels at learning from large amounts of labelled data. Given these capabilities, natural language processing is increasingly applied to new tasks, new domain...
OPENALEX
Open Access
DOI: https://doi.org/10.13025/17598
Hang Li • National Science Review
(2017)
Deep learning refers to machine learning technologies for learning and utilizing ‘deep’ artificial neural networks, such as deep neural networks (DNN), convolutional neural networks (CNN) and recurrent neural networks (RNN). Recently, deep ...
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DOI: https://doi.org/10.1093/nsr/nwx110
Kai Wang, Kunjian Wen, Yanping Chen, Yongbin Qin • Scientific Reports
(2025)
Abstract Mapping a sentence into a two-dimensional (2D) representation can flatten nested semantic structures and build multi-granular span dependencies in named entity recognition. Existing approaches to recognizing named entities often cl...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-87722-0
Muhammad Faseeh, Misbah Bibi, Murad Ali Khan, Atif Rizwan et al. • IEEE Access
(2024)
Accurate depth information is crucial for various computer vision applications such as augmented reality, 3D modeling, and autonomous vehicles. Recent advancements have significantly improved both supervised and self-supervised methods for ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3485089
Neofytos Dimitriou, Ognjen Arandjelović • Information
(2022)
Normalization as a layer within neural networks has over the years demonstrated its effectiveness in neural network optimization across a wide range of different tasks, with one of the most successful approaches being that of batch normaliz...
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Open Access (DOAJ)
DOI: 10.3390/info13070337
Nazeer Bilal, Pradeep Carol Santhosh, Vargas Patricia A., Erden Mustafa Suphi et al. • Manufacturing Review
(2025)
This study presents a comprehensive study of a novel Contact-Based Pose Estimation Method (CBPEM) for enhancing precision in robotic assembly processes within digital twin frameworks. Conventional pose detection methods, such as laser and c...
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Open Access (DOAJ)
DOI: 10.1051/mfreview/2025004
Klemen Istenič, Nuno Gracias, Aurélien Arnaubec, Javier Escartín et al. • Remote Sensing
(2019)
Rapid developments in the field of underwater photogrammetry have given scientists the ability to produce accurate 3-dimensional (3D) models which are now increasingly used in the representation and study of local areas of interest. This pa...
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Open Access (DOAJ)
DOI: 10.3390/rs11182093
Yong Xu, Chaoda Zheng, Ruotao Xu, Yuhui Quan • IEEE Access
(2019)
Recognition of 3D shapes is a fundamental task in computer vision. In recent years, view-based deep learning has emerged as an effective approach for 3D shape recognition. Most existing view-based methods treat the views of an object as an ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2019.2934650
Aleksey Viktorovich Skorokhodov, Sergey Vladimirovich Aksenov, Andrey Vladimirovich Aksenov, Dmitriy Nikolaevich Laykom • Известия Томского политехнического университета: Инжиниринг георесурсов
(2017)
The relevance of the research is caused by the necessity to develop algorithms and software to classify the cloud types based on single-layer cloud on the satellite images received from MODIS spectral radiometer used in Terra and Aqua remot...
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Open Access (DOAJ)
Timothée Corchia, Bertrand Bonan, Nemesio Rodríguez-Fernández, Gabriel Colas et al. • Remote Sensing
(2023)
In this work, Advanced SCATterometer (ASCAT) backscatter data are directly assimilated into the interactions between soil, biosphere, and atmosphere (ISBA) land surface model using Meteo-France’s global Land Data Assimilation System (LDAS-M...
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Open Access (DOAJ)
DOI: 10.3390/rs15174258
Rui Zhang, Ranran Zhou, Zuting Zhong, Haifeng Qi et al. • Sensors
(2024)
Binarized convolutional neural networks (bCNNs) are favored for the design of low-storage, low-power cardiac arrhythmia classifiers owing to their high weight compression rate. However, multi-class classification of ECG signals based on bCN...
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Open Access (DOAJ)
DOI: 10.3390/s24227207
Ye Yuan, Yongtong Zhu, Jiaqi Wang, Ruoshi Li et al. • Frontiers in Neuroscience
(2023)
IntroductionSpiking neural networks (SNNs), inspired by biological neural networks, have received a surge of interest due to its temporal encoding. Biological neural networks are driven by multiple plasticities, including spike timing-depen...
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Open Access (DOAJ)
DOI: 10.3389/fnins.2023.1224752
James Kirkpatrick, Razvan Pascanu, Neil C. Rabinowitz, Joel Veness et al. • Proceedings of the National Academy of Sciences
(2017)
The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitabl...
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Open Access
DOI: https://doi.org/10.1073/pnas.1611835114
PMC: 5380101
Zhiquan He, Meshari Alazmi, Jingfen Zhang, Dong Xu • PLoS ONE
(2013)
Quality assessment (QA) for predicted protein structural models is an important and challenging research problem in protein structure prediction. Consensus Global Distance Test (CGDT) methods assess each decoy (predicted structural model) b...
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Open Access (DOAJ)
DOI: 10.1371/journal.pone.0074006