Results 11 to 20 of about 2,817,119 (330)

Deep Learning in Cardiology [PDF]

IEEE Reviews in Biomedical Engineering, 2021
The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data. Deep learning
Bizopoulos, Paschalis, Koutsouris, Dimitrios   +1 more
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Machine learning and deep learning [PDF]

Electronic Markets, 2021
AbstractToday, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of analytical model building and solve associated tasks.
Christian Janiesch, Patrick Zschech, Kai Heinrich   +2 more
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Deep, deep learning with BART

Magnetic Resonance in Medicine, 2022
PurposeTo develop a deep‐learning‐based image reconstruction framework for reproducible research in MRI.MethodsThe BART toolbox offers a rich set of implementations of calibration and reconstruction algorithms for parallel imaging and compressed sensing.
Blumenthal, Moritz, Luo, Guanxiong, Schilling, Martin, Holme, H. Christian M., Uecker, Martin, Luo, Guanxiong; 1 Institute for Diagnostic and Interventional Radiology University Medical Center Göttingen Göttingen Germany, Schilling, Martin; 1 Institute for Diagnostic and Interventional Radiology University Medical Center Göttingen Göttingen Germany, Holme, H. Christian M.; 2 Institute of Biomedical Imaging Graz University of Technology Graz Austria   +7 more
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Learning Deep Learning

Revista Brasileira de Ensino de Física, 2022
As a consequence of its capability of creating high level abstractions from data, deep learning has been effectively employed in a wide range of applications, including physics. Though deep learning can be, at first and simplistically understood in terms of very large neural networks, it also encompasses new concepts and methods. In order to understand
Arruda, Henrique F. de, Benatti, Alexandre, Comin, César Henrique, Costa, Luciano da F.   +3 more
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Deep learning microscopy [PDF]

Optica, 2017
We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field-of-view and depth-of-field. After its training, the only input to this network is an image acquired using a regular optical microscope, without any changes to its design.
Yair Rivenson, Zoltán Göröcs, Harun Günaydin, Yibo Zhang, Hongda Wang, Aydogan Ozcan   +5 more
openaire   +4 more sources

Deep learning in deep time [PDF]

Proceedings of the National Academy of Sciences, 2020
Digitized natural history records, now numbering in the billions (1), span widely across the tree of life and provide the foundation for numerous recent advances in biodiversity research (2, 3). Mechanistic insights are emerging for old questions, including how diversity has expanded and contracted through Earth’s history (4), how species have come to ...
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Deep learning in bioinformatics [PDF]

Briefings in Bioinformatics, 2016
In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields.
Seonwoo Min, Byunghan Lee, Sungroh Yoon
openaire   +4 more sources

APPLICATION OF DEEP LEARNING

International Journal Vallis Aurea, 2021
In the last decade, there has been a significant increase in the number of papers related to machine learning and the application of machine learning in various fields of science. Belmonte et al. observed that between 2010 and 2018, the growth in the number of papers related to machine learning topics and big data was exponential.
Đokić, Kristian, Mikolcevic, Hrvoje, Šnajder, Ivica   +2 more
openaire   +3 more sources

Deep learning-based anomalous object detection system powered by microcontroller for PTZ cameras [PDF]

, 2018
Automatic video surveillance systems are usually designed to detect anomalous objects being present in a scene or behaving dangerously. In order to perform adequately, they must incorporate models able to achieve accurate pattern recognition in an image,
Benito Picazo, Jesús, Domínguez-Merino, Enrique, López-Rubio, Ezequiel, Ortiz-de-lazcano-Lobato, Juan Miguel, Palomo, Esteban J.   +4 more
core   +1 more source

Deep Learning in Proteomics [PDF]

PROTEOMICS, 2020
AbstractProteomics, the study of all the proteins in biological systems, is becoming a data‐rich science. Protein sequences and structures are comprehensively catalogued in online databases. With recent advancements in tandem mass spectrometry (MS) technology, protein expression and post‐translational modifications (PTMs) can be studied in a variety of
Bo Wen, Wen‐Feng Zeng, Yuxing Liao, Zhiao Shi, Sara R. Savage, Wen Jiang, Bing Zhang   +6 more
openaire   +3 more sources