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pro vyhledávání: '"Sucheta Chauhan"'
Autor:
Sucheta Chauhan, Lovekesh Vig, Michele De Filippo De Grazia, Maurizio Corbetta, Shandar Ahmad, Marco Zorzi
Publikováno v:
Frontiers in Neuroinformatics, Vol 13 (2019)
Stroke causes behavioral deficits in multiple cognitive domains and there is a growing interest in predicting patient performance from neuroimaging data using machine learning techniques. Here, we investigated a deep learning approach based on convol
Externí odkaz:
https://doaj.org/article/a934634cb9d94cf8b06cc56d69dd8135
Publikováno v:
Computers in biology and medicine. 109
Automatic diagnosis of cardiac events is a current problem of interest in which deep learning has shown promising success. We have earlier reported the use of Long Short Term Memory (LSTM) networks-trained on normal ECG patterns-to the detection of a
Publikováno v:
DSAA
Advancement in sequence data generation technologies are churning out voluminous omics data and posing a massive challenge to annotate the biological functional features. Sequence data from the well studied model organism Saccharomyces cerevisiae has
Autor:
Lovekesh Vig, Sucheta Chauhan
Publikováno v:
DSAA
Electrocardiography (ECG) signals are widely used to gauge the health of the human heart, and the resulting time series signal is often analyzed manually by a medical professional to detect any arrhythmia that the patient may have suffered. Much work
Autor:
Sucheta Chauhan, K. V. Prema
Publikováno v:
2013 3rd IEEE International Advance Computing Conference (IACC).
Security is an important concern for today's generation, where keystroke-scan had come out as a milestone. In this paper, a comparison approach is presented for user authentication using keystroke dynamics. Here we have shown the effect of Dimensiona