Zobrazeno 1 - 10
of 22
pro vyhledávání: '"S. Sreedhar Kumar"'
Publikováno v:
In Procedia Computer Science 2024 233:279-287
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:
S. Sreedhar Kumar, Syed Thouheed Ahmed, Qin Xin, S. Sandeep, M. Madheswaran, Syed Muzamil Basha
Publikováno v:
Computers, Materials & Continua. 72:281-299
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31f2085312132438b5387ba158caed1e
https://doi.org/10.32604/cmc.2022.023693
https://doi.org/10.32604/cmc.2022.023693
Publikováno v:
Procedia Computer Science. 215:771-780
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bd814dd5a41d43bbd58e636ddf054d46
https://doi.org/10.1016/j.procs.2022.12.079
https://doi.org/10.1016/j.procs.2022.12.079
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::539447a087412b1020115d4614debd14
https://doi.org/10.1007/s12652-020-02487-w
https://doi.org/10.1007/s12652-020-02487-w
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing. 14:661-661
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0ea35bb5a47a1e9206288abf73229f3f
https://doi.org/10.1007/s12652-022-04305-x
https://doi.org/10.1007/s12652-022-04305-x
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
Publikováno v:
New Trends in Computational Vision and Bio-inspired Computing ISBN: 9783030418618
Data Mining is the procedure of extracting information from a data set and transforms information into comprehensible structure for processing. Clustering is data mining technique used to process data elements into their related groups or partition.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b732757eee791e9556248dac7cc6345
https://doi.org/10.1007/978-3-030-41862-5_114
https://doi.org/10.1007/978-3-030-41862-5_114
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f81e48dfadc621a8b165c08b29f90111
https://doi.org/10.5897/jetr2017.0628
https://doi.org/10.5897/jetr2017.0628
Autor:
S. Sreedhar Kumar, M. Madheswaran
Publikováno v:
2017 Conference on Emerging Devices and Smart Systems (ICEDSS).
In this paper, we present a new approach to reduce the computational complexity of pattern verification and identification through the process of automatically partitioning the existing image feature vector set into highly relative clusters based on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0fc3299057f0dcc5b0d6e0b76496d8f1
https://doi.org/10.1109/icedss.2017.8073693
https://doi.org/10.1109/icedss.2017.8073693