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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...
DOAJ
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...
DOAJ
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
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
Jordan Guerguiev, Timothy Lillicrap, Blake A. Richards • eLife
(2017)
Deep learning has led to significant advances in artificial intelligence, in part, by adopting strategies motivated by neurophysiology. However, it is unclear whether deep learning could occur in the real brain. Here, we show that a deep le...
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DOI: https://doi.org/10.7554/elife.22901
PMC: 5716677
Jan Kukačka, Vladimir Golkov, Daniel Cremers • arXiv (Cornell University)
(2017)
Regularization is one of the crucial ingredients of deep learning, yet the term regularization has various definitions, and regularization methods are often studied separately from each other. In our work we present a systematic, unifying t...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1710.10686
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
Bryan Y. Lim, Stefan Zohren • Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
(2021)
Numerous deep learning architectures have been developed to accommodate the diversity of time-series datasets across different domains. In this article, we survey common encoder and decoder designs used in both one-step-ahead and multi-hori...
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Open Access
DOI: https://doi.org/10.1098/rsta.2020.0209
Jürgen Schmidhuber • Neural Networks
(2014)
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Open Access
DOI: https://doi.org/10.1016/j.neunet.2014.09.003
Lin Bing, Tan Xiao, He Kai, Wu Huaming • Tongxin xuebao
(2026)
Satellite edge computing faces a trade-off between privacy protection and system overhead, strict task-dependency constraints, and the limited ability of conventional algorithms to capture complex dependency topologies in digital twin task ...
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Open Access (DOAJ)
Meirong ZHANG, Mengting HAO, Chuang WANG, Gengxin ZHANG • 天地一体化信息网络
(2021)
With the vigorous development of space communication technology and the continuous advancement of space-integrated-ground information network, satellite communication networks resource management and control is becoming more and more comple...
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Open Access (DOAJ)
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
Hao Shi, Guo Cao, Youqiang Zhang, Zixian Ge et al. • Remote Sensing
(2022)
Deep learning (DL) has recently been a core ingredient in modern computer vision tasks, triggering a wave of revolutions in various fields. The hyperspectral image (HSI) classification task is no exception. A wide range of DL-based methods ...
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Open Access (DOAJ)
DOI: 10.3390/rs14174235
Qing Chen, Aihuang Guo, Yaodong Cui • Applied Sciences
(2024)
To achieve the anticipated performance of massive multiple input multiple output (MIMO) systems in wireless communication, it is imperative that the user equipment (UE) accurately feeds the channel state information (CSI) back to the base s...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app14041356
Zhi He, Chengle Zhou, Liwei Zou, Suhong Zhou et al. • International Journal of Digital Earth
(2025)
Accurately monitoring disaster effects is a crucial task in relief efforts (e.g. typhoon rescue). Social media data plays a vital role in disaster management, while deep learning-based methods gain more attention in typhoon disaster researc...
DOAJ
Open Access (DOAJ)
DOI: 10.1080/17538947.2025.2517790
Chen Chen, Rufei Fu, Xiaojian Ai, Chengbin Huang et al. • Remote Sensing
(2022)
Water conservancy personnel usually need to know the water level by water gauge images in real-time and with an expected accuracy. However, accurately recognizing the water level from water gauge images is still a complex problem. This arti...
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Open Access (DOAJ)
DOI: 10.3390/rs14236023
Jürgen Franke, Wolfgang Karl Härdle, Christian Matthias Hafner • Universitext
(2019)
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DOI: https://doi.org/10.1007/978-3-030-13751-9_19
Amirhossein Tavanaei, Masoud Ghodrati, Saeed Reza Kheradpisheh, Timothée Masquelier et al. • Neural Networks
(2018)
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Open Access
DOI: https://doi.org/10.1016/j.neunet.2018.12.002
Anton S. Becker, Magda Marcon, Soleen Ghafoor, Moritz C. Wurnig et al. • Investigative Radiology
(2017)
OBJECTIVES: The aim of this study was to evaluate the diagnostic accuracy of a multipurpose image analysis software based on deep learning with artificial neural networks for the detection of breast cancer in an independent, dual-center mam...
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DOI: https://doi.org/10.1097/rli.0000000000000358
Rocio Vargas, Amir Hosein Mosavi, Ramon Ruiz • Preprints.org
(2018)
Deep learning is an emerging area of machine learning (ML) research. It comprises multiple hidden layers of artificial neural networks. The deep learn- ing methodology applies nonlinear transformations and model abstractions of high level i...
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DOI: https://doi.org/10.20944/preprints201810.0218.v1