Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Sittampalam Sotheeswaran"'
Autor:
Logiraj Kumaralingam, Kokul Thanikasalam, Sittampalam Sotheeswaran, Jeyasuthan Mahadevan, Nagulan Ratnarajah
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031164309
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::545f4e78077aa3d99ab6438a042789e1
https://doi.org/10.1007/978-3-031-16431-6_18
https://doi.org/10.1007/978-3-031-16431-6_18
Publikováno v:
2021 21st International Conference on Advances in ICT for Emerging Regions (ICter).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c1dce530e011cdd3c59b2fe75bf5d80
https://doi.org/10.1109/icter53630.2021.9774801
https://doi.org/10.1109/icter53630.2021.9774801
Publikováno v:
2021 10th International Conference on Information and Automation for Sustainability (ICIAfS).
The tract-based white matter analysis is an effective framework to study the structural brain using quantitative parameters of interest along with major fibre bundles. Accurate and consistent clustering of brain white matter bundles from the whole br
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3524bd7b1a73e54b0832a433eaaec23
https://doi.org/10.1109/iciafs52090.2021.9606130
https://doi.org/10.1109/iciafs52090.2021.9606130
Publikováno v:
2020 20th International Conference on Advances in ICT for Emerging Regions (ICTer).
The greatest common divisor (GCD) is used for numerous applications in number theory, modular arithmetic, encryption algorithms such as RSA, random number generation, and solving linear Diophantine equations. High-performance algorithms, which are ef
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::810e4d631776825fb2cf0954417f8c48
https://doi.org/10.1109/icter51097.2020.9325430
https://doi.org/10.1109/icter51097.2020.9325430
Novel computational approaches for border irregularity prediction to detect melanoma in skin lesions
Publikováno v:
2020 International Research Conference on Smart Computing and Systems Engineering (SCSE).
Medical image detection has been a rapidly growing field of study during the last few years. There are different challenges associated with it. Many works have been done in order to provide solutions for key challenges. This study of work is focused
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffb5f6793d09c38b6c4e9a7a0c292355
https://doi.org/10.1109/scse49731.2020.9313042
https://doi.org/10.1109/scse49731.2020.9313042
Publikováno v:
Pattern Recognition and Image Analysis. 28:142-154
This paper proposes a vehicle logo recognition (VLR) system centered on front-view cars, which has been largely neglected by vision community in comparison to other object recognition tasks. The study focuses on local features that describe structura
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad2c2a1d5f1578d16b79d25f056a2ff5
https://doi.org/10.1134/s1054661818010170
https://doi.org/10.1134/s1054661818010170
Publikováno v:
2015 Fifteenth International Conference on Advances in ICT for Emerging Regions (ICTer).
Vehicle detection has received much attention over the recent years. In this paper we mainly address on the detection of cars in front-view static images and focus on local features that describe structural characteristics in particular. Our method i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f86ad90b8aa6d39ebdfe9c56726139ea
https://doi.org/10.1109/icter.2015.7377660
https://doi.org/10.1109/icter.2015.7377660
Publikováno v:
2014 9th International Conference on Industrial and Information Systems (ICIIS).
Logo identification and classification have received considerable attention from both the machine learning and computer vision communities. Vehicle logo recognition (VLR) is used to recognise accurately the manufacturer of a vehicle by using its icon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::69de297b4999a0dc0c23ef5e659ca843
https://doi.org/10.1109/iciinfs.2014.7036486
https://doi.org/10.1109/iciinfs.2014.7036486