Zobrazeno 1 - 10
of 25
pro vyhledávání: '"S, Sreedhar Kumar"'
Publikováno v:
In Procedia Computer Science 2024 233:279-287
Autor:
S., Sreedhar Kumar, Ahmed, Syed Thouheed, Fathima, Afifa Salsabil, Mathivanan, Sandeep Kumar, Jayagopal, Prabhu, Saif, Abdu, Gupta, Sachin Kumar, Sinha, Garima
Publikováno v:
Multimedia Tools & Applications; Nov2024, Vol. 83 Issue 39, p86359-86381, 23p
Autor:
S, Sreedhar Kumar, M, Gunashree, Ahmed, Syed Thouheed, M, Sindhuja, P, Bhumika, B, Anusha, B, Ishwarya
Publikováno v:
In Procedia Computer Science 2020 171:1624-1633
Autor:
Thouheed Ahmed, Syed, Kumari Patil, Kiran, S., Sreedhar Kumar, Kumar Dhanaraj, Rajesh, Bhatia Khan, Surbhi, Alzahrani, Saeed, Rani, Shalli
Publikováno v:
IEEE Transactions on Consumer Electronics; August 2024, Vol. 70 Issue: 3 p5524-5532, 9p
Publikováno v:
Procedia Computer Science. 215:771-780
Autor:
S. Sreedhar Kumar, Syed Thouheed Ahmed, Qin Xin, S. Sandeep, M. Madheswaran, Syed Muzamil Basha
Publikováno v:
Computers, Materials & Continua. 72:281-299
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing. 12:7581-7594
This paper presents an improved cluster validation scheme called two phase cluster validation (TPCV) and aims to estimate the inter closeness and inter separation among the clusters in the cluster set of unsupervised clustering schemes based on proba
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing. 14:661-661
Publikováno v:
Advances in Automation, Signal Processing, Instrumentation, and Control ISBN: 9789811582202
The compressed sensing is a mathematical approach of reconstructing a signal that is acquired from the dimensionally reduced data coefficients/less number of samples, i.e., less than the Niquist rate. The data coefficients are high-frequency componen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::95eb94c0ecdcbb864f346c6dee6e44e3
https://doi.org/10.1007/978-981-15-8221-9_265
https://doi.org/10.1007/978-981-15-8221-9_265
Autor:
S Sreedhar Kumar, M. Madheswaran
Publikováno v:
Journal of Engineering and Technology Research. 9:30-41
In this study, a frequency based Dynamic Automatic Agglomerative Clustering (DAAC) is developed and presented. The DAAC scheme aims to automatically identify the appropriate number of divergent clusters over the two dimensional dataset based on count