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Academic Articles & Research Papers
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Michele Avanzo, Lise Wei, Joseph Stancanello, Martin Vallières et al. • Medical Physics
(2020)
Radiomics is an emerging area in quantitative image analysis that aims to relate large-scale extracted imaging information to clinical and biological endpoints. The development of quantitative imaging methods along with machine learning has...
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DOI: https://doi.org/10.1002/mp.13678
PMC: 8965689
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
Yan Wang, Hao Zhang, Wei Huang, Manli Zhou et al. • Frontiers in Marine Science
(2024)
The critical nature of passive ship-radiated noise recognition for military and economic security is well-established, yet its advancement faces significant obstacles due to the complex marine environment. The challenges include natural sou...
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Open Access (DOAJ)
DOI: 10.3389/fmars.2024.1334057
Sheng Zhang, Zhenghao Bei, Tonghua Ling, Qianqian Chen et al. • Scientific Reports
(2024)
Abstract Accurate detection of asphalt pavement distress is crucial for road maintenance and traffic safety. However, traditional convolutional neural networks usually struggle with this task due to the varied distress patterns and complex ...
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Open Access (DOAJ)
DOI: 10.1038/s41598-024-77173-4
Wei Zhang, Chao Ren, Haoming Bai, Huada Huang et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2026)
Accurate monitoring of the spatial extent of sugarcane cultivation is critical for optimizing land-use efficiency and regulating the sugar industry. However, sugarcane cultivation areas are characterized by complex topography and fragmented...
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Open Access (DOAJ)
DOI: 10.1109/JSTARS.2026.3716367
Samane Esmaelzade Kalkhoran, Seyyed Saeed Ghannadpour • Scientific Reports
(2026)
Abstract Porphyry Cu deposits in the Urmia–Dokhtar magmatic belt constitute important exploration targets, yet the heterogeneous and multi-scale nature of geological, geochemical, and remote sensing data introduces substantial uncertainty i...
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Open Access (DOAJ)
DOI: 10.1038/s41598-026-61085-6
A. Geiss, S. J. Silva, S. J. Silva, J. C. Hardin et al. • Geoscientific Model Development
(2022)
Recent advances in deep convolutional neural network (CNN)-based super resolution can be used to downscale atmospheric chemistry simulations with substantially higher accuracy than conventional downscaling methods. This work both demonstrat...
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Open Access (DOAJ)
DOI: 10.5194/gmd-15-6677-2022
saeedeh zebhi, Seyed Mohammad Taghi AlModaressi, Vahid Abootalebi • AUT Journal of Electrical Engineering
(2021)
In this paper, two different methods of human activity recognition based on video signals are introduced. The first method explores the effectiveness of combining feature descriptors obtained by local descriptors and artificial neural network ...
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Open Access (DOAJ)
DOI: 10.22060/eej.2020.18517.5357
Jason Riordon, Dušan Sovilj, Scott Sanner, David A. Sinton et al. • Trends in biotechnology
(2018)
Advances in high-throughput and multiplexed microfluidics have rewarded biotechnology researchers with vast amounts of data but not necessarily the ability to analyze complex data effectively. Over the past few years, deep artificial neural...
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DOI: https://doi.org/10.1016/j.tibtech.2018.08.005
Zhihao Wang, Jian Chen, Steven C. H. Hoi • IEEE Transactions on Pattern Analysis and Machine Intelligence
(2020)
Image Super-Resolution (SR) is an important class of image processing techniqueso enhance the resolution of images and videos in computer vision. Recent years have witnessed remarkable progress of image super-resolution using deep learning ...
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Open Access
DOI: https://doi.org/10.1109/tpami.2020.2982166
Christopher D. Manning • Computational Linguistics
(2015)
Deep Learning waves have lapped at the shores of computational linguistics for several years now, but 2015 seems like the year when the full force of the tsunami hit the major Natural Language Processing (NLP) conferences. However, some pun...
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Open Access
DOI: https://doi.org/10.1162/coli_a_00239
Jing Li, Aixin Sun, Jianglei Han, Chenliang Li • IEEE Transactions on Knowledge and Data Engineering
(2020)
Named entity recognition (NER) is the task to identify mentions of rigid designators from text belonging to predefined semantic types such as person, location, organization etc. NER always serves as the foundation for many natural language ...
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Open Access
DOI: https://doi.org/10.1109/tkde.2020.2981314
Ruihui Mu, Xiaoqin Zeng • KSII Transactions on Internet and Information Systems
(2019)
With the advent of big data, deep learning technology has become an important research direction in the field of machine learning, which has been widely applied in the image processing, natural language processing, speech recognition and on...
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Open Access
DOI: https://doi.org/10.3837/tiis.2019.04.001
Xue-Wen Chen, Xiaotong Lin • IEEE Access
(2014)
Deep learning is currently an extremely active research area in machine learning and pattern recognition society. It has gained huge successes in a broad area of applications such as speech recognition, computer vision, and natural language...
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Open Access
DOI: https://doi.org/10.1109/access.2014.2325029
ZHANG Bin1, YIN Haoyu2, ZHANG Tengfei2, WANG Jiangyu1, LU Di1, WANG Lianjie1 • Yuanzineng kexue jishu
(2026)
To meet the computational efficiency requirements for multi-physics simulations in the design and development of advanced reactor cores, a neural network-based acceleration method was investigated for multi-physics coupling calculations in ...
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Open Access (DOAJ)
DOI: 10.7538/yzk.2025.youxian.0668
Xiaofeng Li, Bo Peng, Xinyu Li, Zhenghan Wang et al. • Scientific Reports
(2026)
Abstract Hypertrophic Cardiomyopathy (HCM) and Cardiac Amyloidosis (CA) are two cardiac conditions that can advance to heart failure if left untreated, which present considerable diagnostic challenges due to their overlapping echocardiograp...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-15443-5
Chun-Wei Huang, Si Ying Yau, Chiao-Ling Kuo, Tsai-Yu Kuan et al. • Journal of Hydrology: Regional Studies
(2024)
Study region: The Choushui River Fan, Taiwan. Study focus: Groundwater overdraft has led to not only groundwater depletion but also environmental disasters, such as subsidence and seawater intrusion in the Choushui River Alluvial Fan, Taiwa...
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Open Access (DOAJ)
DOI: 10.1016/j.ejrh.2023.101636
Fotios S. Konstantakopoulos, Eleni I. Georga, Dimitrios I. Fotiadis • IEEE Open Journal of Engineering in Medicine and Biology
(2023)
Goal: The modern way of living has significantly influenced the daily diet. The ever-increasing number of people with obesity, diabetes and cardiovascular diseases stresses the need to find tools that could help in the daily intake of the n...
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Open Access (DOAJ)
DOI: 10.1109/OJEMB.2023.3266135
Ahmad Mohsenimanesh, Evgueniy Entchev, Filip Bosnjak • Applied Sciences
(2022)
Forecasting the aggregate charging load of a fleet of electric vehicles (EVs) plays an important role in the energy management of the future power system. Therefore, accurate charging load forecasting is necessary for reliable and efficient...
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Open Access (DOAJ)
DOI: 10.3390/app12189288
Murat Sari, Arshed A. Ahmad • International Journal of Analysis and Applications
(2019)
The aim of this article is to forecast anemia from a population through biomedical variables of individuals using the multiple linear regression model. The study is conducted in terms of dataset consisting of 539 subjects provided from bloo...
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Open Access (DOAJ)