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Showing 20 of 2,024 academic articles
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 ...
DOAJ
Open Access (DOAJ)
DOI: 10.22060/eej.2020.18517.5357
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
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
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
Athanasios S. Voulodimos, Nikolaos D. Doulamis, Anastasios D. Doulamis, Eftychios E. Protopapadakis • Computational Intelligence and Neuroscience
(2018)
Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief ...
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DOI: https://doi.org/10.1155/2018/7068349
PMC: 5816885
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
Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup et al. • Neural Networks
(2022)
Deep learning (DL) and reinforcement learning (RL) methods seem to be a part of indispensable factors to achieve human-level or super-human AI systems. On the other hand, both DL and RL have strong connections with our brain functions and w...
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cc-by-nc-nd
DOI: https://doi.org/10.1016/j.neunet.2022.03.037
Chensi Cao, Feng Liu, Hai Tan, Deshou Song et al. • Genomics Proteomics & Bioinformatics
(2018)
Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitat...
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DOI: https://doi.org/10.1016/j.gpb.2017.07.003
PMC: 6000200
Noritaka Fukunaga, Sho Sanami, Hiroya Kitasaka, Yuji Tsuzuki et al. • Reproductive Medicine and Biology
(2020)
Abstract Purpose To establish an automated pronuclei determination system by analysis using deep learning technology which is able to effectively learn with limited amount of supervised data. Methods An algorithm was developed by explicitly...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/rmb2.12331
Pramila P. Shinde, Seema Shah • International Conference on Computing Communication Control and automation
(2018)
Machine learning is one of the fields in the modern computing world. A plenty of research has been undertaken to make machines intelligent. Learning is a natural human behavior which has been made an essential aspect of the machines as well...
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DOI: https://doi.org/10.1109/iccubea.2018.8697857
Polina Mamoshina, Armando S. Vieira, Eugene Lane, Alex A. Zhavoronkov • Molecular Pharmaceutics
(2016)
Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this ...
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DOI: https://doi.org/10.1021/acs.molpharmaceut.5b00982
Sylvain Christin, Éric Hervet, Nicolas Lecomte • Methods in Ecology and Evolution
(2019)
Abstract A lot of hype has recently been generated around deep learning, a group of artificial intelligence approaches able to break accuracy records in pattern recognition. Over the course of just a few years, deep learning revolutionized ...
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Open Access
DOI: https://doi.org/10.1111/2041-210x.13256
Neil Thompson, Kristjan H. Greenewald, Keeheon Lee, Gabriel F. Manso (2023)
Deep learning's recent history has been one of achievement: from triumphing over humans in the game of Go to world-leading performance in image classification, voice recognition, translation, and other tasks.But this progress has come with ...
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DOI: https://doi.org/10.21428/bf6fb269.1f033948
Terrence J. Sejnowski A B • The MIT Press eBooks
(2018)
How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy.The deep learning revolution has brought us driverless cars, the greatly improved...
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DOI: https://doi.org/10.7551/mitpress/11474.001.0001
Shiv Singh, Neelu Jyothi Ahuja • Discover Computing
(2026)
Abstract The application of deep learning models in resource-constrained environments requires a trade-off among accuracy, efficiency, and interpretability a trilemma frequently neglected in conventional knowledge distillation (KD) approach...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s10791-026-10123-y
Natasha Dropka, Stefan Ecklebe, Martin Holena • Crystals
(2021)
The aim of this study was to assess the aptitude of the recurrent Long Short-Term Memory (LSTM) neural networks for fast and accurate predictions of process dynamics in vertical-gradient-freeze growth of gallium arsenide crystals (VGF-GaAs)...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/cryst11020138
Ian Goodfellow, Yoshua Bengio, Aaron C. Courville • The MIT Press eBooks
(2016)
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human c...
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DOI: https://doi.org/10.1016/b978-0-12-804291-5.00010-6
Dimitrios Papamartzivanos, Felix Gomez Marmol, Georgios Kambourakis • IEEE Access
(2019)
The intrusion detection systems (IDSs) are essential elements when it comes to the protection of an ICT infrastructure. A misuse IDS is a stable method that can achieve high attack detection rates (ADR) while keeping false alarm rates under...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2019.2893871
Charles Nicholson, Lex Beattie, Matthew Beattie, Talayeh Razzaghi et al. • PLoS ONE
(2022)
COVID-19 is a global pandemic threatening the lives and livelihood of millions of people across the world. Due to its novelty and quick spread, scientists have had difficulty in creating accurate forecasts for this disease. In part, this is...
DOAJ
Open Access (DOAJ)
DOI: 10.1371/journal.pone.0267558