Zobrazeno 1 - 10
of 733
pro vyhledávání: '"S Vivek"'
Autor:
Ashish Kumar Jain, C Manchanda Subhash, S Vivek Bhola, Madan Kushal, Mehta Ashwini, S Sawhney Jitendrapal
Publikováno v:
International Journal of Yoga, Vol 15, Iss 1, Pp 40-44 (2022)
Background: In spite of significant advances in the management of heart failure (HF), morbidity and mortality remain high. Therefore, there is a need for additional strategies. We did a randomized clinical trial to study effect of yoga in patients wi
Externí odkaz:
https://doaj.org/article/3f0e8f1054724f20aa5e4c61b686f43c
Publikováno v:
Indian Journal of Community Medicine, Vol 43, Iss 1, Pp 49-52 (2018)
Background: Depression often interferes with self-management and treatment of medical conditions. This may result in serious medical complications and escalated health-care cost. Objectives: Study distribution of heart failure (HF) cases estimates th
Externí odkaz:
https://doaj.org/article/587cfb04ce3b42d4b107230e54d4d40c
Autor:
R Senthilnathan, S Vivek
Publikováno v:
Journal of Indian Association of Pediatric Surgeons, Vol 21, Iss 1, Pp 36-37 (2016)
We report a case of dermoid cyst in an undescended intra-abdominal testis, which presented with torsion and gangrene.
Externí odkaz:
https://doaj.org/article/8453d3c5ef794bd0980f08e620a287ba
Autor:
S., Vivek B., Babu, R. Venkatesh
Deep learning models have shown impressive performance across a spectrum of computer vision applications including medical diagnosis and autonomous driving. One of the major concerns that these models face is their susceptibility to adversarial attac
Externí odkaz:
http://arxiv.org/abs/2004.08628
As humans, we inherently perceive images based on their predominant features, and ignore noise embedded within lower bit planes. On the contrary, Deep Neural Networks are known to confidently misclassify images corrupted with meticulously crafted per
Externí odkaz:
http://arxiv.org/abs/2004.00306
Akademický článek
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Autor:
S, Vivek, R, Umamaheswari, P, Subashree, S, Rajakumar, P, Mukesh, V, Priya, V, Sampathkumar, N, Logesh, Prabhu G, Ganesh
Publikováno v:
In Environmental Research 1 January 2024 240 Part 1
Adversarial samples are perturbed inputs crafted to mislead the machine learning systems. A training mechanism, called adversarial training, which presents adversarial samples along with clean samples has been introduced to learn robust models. In or
Externí odkaz:
http://arxiv.org/abs/1808.01753
Autor:
Sundar S., Nair Syam, Surana, Prashant, R. S., Vivek, T. P., Vaidika, Gopakumar, K., Umanand, L.
Publikováno v:
IEEE Transactions on Industrial Electronics; December 2024, Vol. 71 Issue: 12 p15415-15423, 9p
Akademický článek
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