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Academic Articles & Research Papers
Showing 20 of 3,028 academic articles
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
Johannes L. Otto, Lukas M. Sauer, Malte Brink, Thorge Schaum et al. • Materials & Design
(2023)
Nickel-based filler metals are frequently used in high temperature vacuum diffusion brazing for austenitic stainless-steel joints when components are subjected to high static or dynamic loads, corrosive environments and elevated temperature...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.matdes.2023.112401
Sheng Ren, Rui Cao, Wenxue Tan, Yayuan Tang • IEEE Access
(2024)
The single image super-resolution based on deep learning has achieved extraordinary performance. However, due to inevitable environmental or technological limitations, some images not only have low resolution but also low brightness. The ex...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3403096
Francis Quintal Lauzon • International Conference on Information Science, Signal Processing and their Applications (ISSPA)
(2012)
Deep learning allows automatically learning multiple levels of representations of the underlying distribution of the data to be modeled. In this work, a specific implementation called stacked denoising autoencoders is explored. We contribut...
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DOI: https://doi.org/10.1109/isspa.2012.6310529
Andreas Mayr, Günter Klambauer, Thomas Unterthiner, Sepp Hochreiter • Frontiers in Environmental Science
(2016)
The Tox21 Data Challenge has been the largest effort of the scientific community to compare computational methods for toxicity prediction. This challenge comprised 12,000 environmental chemicals and drugs which were measured for 12 differen...
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DOI: https://doi.org/10.3389/fenvs.2015.00080
Qiang Zhao, Rundong Guo, Xiaowei Feng, Weifeng Hu et al. • Mathematics
(2022)
Legal judgement prediction (LJP) is a crucial part of legal AI, and its goal is to predict the outcome of a case based on the information in the description of criminal facts. This paper proposes a decision prediction method based on causal...
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Open Access (DOAJ)
DOI: 10.3390/math10132281
Sidharth Mudgal, Han Li, Theodoros Rekatsinas, AnHai Doan et al. • ACM SIGMOD International Conference on Management of Data (SIGMOD)
(2018)
Entity matching (EM) finds data instances that refer to the same real-world entity. In this paper we examine applying deep learning (DL) to EM, to understand DL's benefits and limitations. We review many DL solutions that have been develope...
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DOI: https://doi.org/10.1145/3183713.3196926
Shutao Li A, Weiwei Song, Leyuan Fang, Yushi Chen et al. • IEEE Transactions on Geoscience and Remote Sensing
(2019)
Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of hyperspectral data make the accurate classification of such data challenging for traditional machine ...
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Open Access
DOI: https://doi.org/10.1109/tgrs.2019.2907932
Travers H. Ching, Daniel Scott Himmelstein, Brett K. Beaulieu‐Jones, Alexandr A. Kalinin et al. • Journal of The Royal Society Interface
(2018)
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and m...
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DOI: https://doi.org/10.1098/rsif.2017.0387
PMC: 5938574
Lei Zhou, Chu Zhang, Fei Liu, Zhengjun Qiu et al. • Comprehensive Reviews in Food Science and Food Safety
(2019)
Deep learning has been proved to be an advanced technology for big data analysis with a large number of successful cases in image processing, speech recognition, object detection, and so on. Recently, it has also been introduced in food sci...
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DOI: https://doi.org/10.1111/1541-4337.12492
Yu Lyu, Xiaolin Tian • Bioengineering
(2023)
Deep learning technology has achieved breakthrough research results in the fields of medical computer vision and image processing. Generative adversarial networks (GANs) have demonstrated a capacity for image generation and expression abili...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/bioengineering10091091
Andrea Steuwe, Birte Valentin, Oliver T. Bethge, Alexandra Ljimani et al. • Diagnostics
(2022)
Deep-learning (DL) noise reduction techniques in computed tomography (CT) are expected to reduce the image noise while maintaining the clinically relevant information in reduced dose acquisitions. This study aimed to assess the size, attenu...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/diagnostics12071627
Ajantha Vijayakumar, Joseph Abraham Sundar Koilraj, Muthaiah Rajappa • International Journal of Computational Intelligence Systems
(2025)
Abstract Oral dosage forms are the most widely employed method of drug delivery in therapeutic treatments. However, the presence of visual defects in blister packages can adversely affect the drug's bioavailability and therapeutic efficacy,...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44196-025-00986-2
RenHui Wu, MengMeng Yang, TianChi Wu, RongZhen Li et al. • PeerJ
(2026)
Background In recent years, skin health has garnered widespread attention, with hyperpigmentation disorders caused by excessive melanin deposition emerging as a particularly prominent concern. Tyrosinase, as the rate-limiting enzyme in the ...
DOAJ
Open Access (DOAJ)
DOI: 10.7717/peerj.20845
Hairu Luo, Peng Jia, Anmin Zhou, Yuying Liu et al. • Applied Sciences
(2022)
In a complex network, some nodes are relatively concentrated in topological structure, thus forming a relatively independent node group, which we call a community. Usually, there are multiple communities on a network, and these communities ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app122010337
Jeffrey C. Kimmel, Andrew D. Mcdole, Mahmoud Abdelsalam, Maanak Gupta et al. • IEEE Access
(2021)
Several organizations are utilizing cloud technologies and resources to run a range of applications. These services help businesses save on hardware management, scalability and maintainability concerns of underlying infrastructure. Key clou...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2021.3077498
Sergey Plis, Devon Hjelm, Ruslan Salakhutdinov, Elena A. Allen et al. • Frontiers in Neuroscience
(2014)
Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neu...
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DOI: https://doi.org/10.3389/fnins.2014.00229
PMC: 4138493
Ruud J. G. van Sloun, Regev Cohen, Yonina C. Eldar • Proceedings of the IEEE
(2019)
In this article, we consider deep learning strategies in ultrasound systems, from the front end to advanced applications. Our goal is to provide the reader with a broad understanding of the possible impact of deep learning methodologies on ...
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Open Access
DOI: https://doi.org/10.1109/jproc.2019.2932116
Connor Shorten, Taghi M. Khoshgoftaar, Borko Furht • Journal Of Big Data
(2021)
Natural Language Processing (NLP) is one of the most captivating applications of Deep Learning. In this survey, we consider how the Data Augmentation training strategy can aid in its development. We begin with the major motifs of Data Augme...
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DOI: https://doi.org/10.1186/s40537-021-00492-0
PMC: 8287113