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Xiaoxiao Ma, Jia Xin Wu, Shan Xue, Jian Yu Yang et al. • IEEE Transactions on Knowledge and Data Engineering
(2021)
Anomalies are rare observations (e.g., data records or events) that deviate significantly from the others in the sample. Over the past few decades, research on anomaly mining has received increasing interests due to the implications of thes...
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Open Access
DOI: https://doi.org/10.1109/tkde.2021.3118815
Siwei Yu, Jianwei Ma • Reviews of Geophysics
(2021)
Abstract Recently deep learning (DL), as a new data‐driven technique compared to conventional approaches, has attracted increasing attention in geophysical community, resulting in many opportunities and challenges. DL was proven to have the...
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DOI: https://doi.org/10.1029/2021rg000742
Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai et al. • npj Digital Medicine
(2018)
Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variabl...
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DOI: https://doi.org/10.1038/s41746-018-0029-1
PMC: 6550175
Xiao Xiang Zhu, Devis Tuia, Lichao Mou, Gui-Song Xia et al. • IEEE Geoscience and Remote Sensing Magazine
(2017)
Central to the looming paradigm shift toward data-intensive science, machine-learning techniques are becoming increasingly important. In particular, deep learning has proven to be both a major breakthrough and an extremely powerful tool in ...
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Open Access
DOI: https://doi.org/10.1109/mgrs.2017.2762307
Changchun Yang, Hengrong Lan, Feng Gao, Fei Gao • Photoacoustics
(2020)
Machine learning has been developed dramatically and witnessed a lot of applications in various fields over the past few years. This boom originated in 2009, when a new model emerged, that is, the deep artificial neural network, which began...
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DOI: https://doi.org/10.1016/j.pacs.2020.100215
PMC: 7779783
WANG Ziyi, GUO Shaoyong, CHEN Jiewei, XIAO Yitao et al. • Tongxin xuebao
(2026)
With the rapid growth of AI, data-center energy consumption continues to increase. To balance computing service requirements and renewable-energy fluctuations, a grid carbon-intensity-aware power–computing coordinated scheduling method was ...
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Open Access (DOAJ)
Petryshyna Olga, Boyko Mariya • SHS Web of Conferences
(2021)
In modern academic community not only communication management plays a great role. Monitoring of expectations, awareness of communicative needs, the course and results of communicative interaction, barriers hindering rational managerial dec...
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Open Access (DOAJ)
DOI: 10.1051/shsconf/202110402012
Junpo Yu, Yajun Si, Wen Zhao, Zeyu Zhou et al. • Plants
(2025)
As the world’s largest loess deposit region, the Loess Plateau’s vegetation dynamics are crucial for its regional water–heat balance and ecosystem functioning. Leaf Area Index (LAI) serves as a key indicator bridging canopy architecture and...
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Open Access (DOAJ)
DOI: 10.3390/plants14152391
Aziz Siyaev, Geun-Sik Jo • IEEE Access
(2021)
In the emerging world of metaverses, it is essential for speech communication systems to be aware of context to interact with virtual assets in the 3D world. This paper proposes the metaverse for aircraft maintenance training and education ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2021.3128616
Gaurav Menghani • ACM Computing Surveys
(2023)
Deep learning has revolutionized the fields of computer vision, natural language understanding, speech recognition, information retrieval, and more. However, with the progressive improvements in deep learning models, their number of paramet...
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Open Access
DOI: https://doi.org/10.1145/3578938
Christopher Ardohain, Songlin Fei • Science of Remote Sensing
(2025)
Deep learning (DL) is ubiquitous in remote sensing analysis with continued evolution in model architectures and advancement of model types. However, DL is still constrained by the need for extensive training datasets, which are costly and t...
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Open Access (DOAJ)
DOI: 10.1016/j.srs.2024.100185
Mufti Mahmud, M. Shamim Kaiser, T. Martin McGinnity, Amir Hussain • Cognitive Computation
(2021)
Recent technological advancements in data acquisition tools allowed life scientists to acquire multimodal data from different biological application domains. Categorized in three broad types (i.e. images, signals, and sequences), these data...
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DOI: https://doi.org/10.1007/s12559-020-09773-x
PMC: 7783296
Alexander Selvikvåg Lundervold, Arvid Lundervold • Zeitschrift für Medizinische Physik
(2018)
What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started around 2009 when...
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DOI: https://doi.org/10.1016/j.zemedi.2018.11.002
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
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
Gustau Camps‐Valls, Devis Tuia, Xiao Xiang Zhu, Markus Reichstein • Wiley eBooks
(2021)
Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only re...
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Open Access
DOI: https://doi.org/10.1002/9781119646181
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
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
Jing Liu, Xuesong Hai, Keqin Li • Future Internet
(2023)
Massive amounts of data drive the performance of deep learning models, but in practice, data resources are often highly dispersed and bound by data privacy and security concerns, making it difficult for multiple data sources to share their ...
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Open Access (DOAJ)
DOI: 10.3390/fi16010006
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)