Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Saravana Balaji Balasubramanian"'
Publikováno v:
PeerJ Computer Science, Vol 10, p e2093 (2024)
In the realm of multi-label learning, instances are often characterized by a plurality of labels, diverging from the single-label paradigm prevalent in conventional datasets. Multi-label techniques often employ a similar feature space to build classi
Externí odkaz:
https://doaj.org/article/4650588499d949c69282f09efb50f3b0
Autor:
Saravana Balaji Balasubramanian, Prasanalakshmi Balaji, Asmaa Munshi, Wafa Almukadi, T. N. Prabhu, Venkatachalam K, Mohamed Abouhawwash
Publikováno v:
PeerJ Computer Science, Vol 9, p e1259 (2023)
In smart cities, the fast increase in automobiles has caused congestion, pollution, and disruptions in the transportation of commodities. Each year, there are more fatalities and cases of permanent impairment due to everyday road accidents. To contro
Externí odkaz:
https://doaj.org/article/21eff6544e1b4da7828e2d11660b5053
Autor:
Saravana Balaji Balasubramanian, Jagadeesh Kannan R, Prabu P, Venkatachalam K, Pavel Trojovský
Publikováno v:
PeerJ Computer Science, Vol 8, p e1040 (2022)
In the recent research era, artificial intelligence techniques have been used for computer vision, big data analysis, and detection systems. The development of these advanced technologies has also increased security and privacy issues. One kind of th
Externí odkaz:
https://doaj.org/article/571ef014727a481cbd595bf2e247e166
Publikováno v:
International Journal of Cloud Computing. 12:191
Publikováno v:
International Journal of Advanced Trends in Computer Science and Engineering. 8:80-90
Publikováno v:
International Journal of Advanced Trends in Computer Science and Engineering. 8:18-22
Autor:
Mohamed Uvaze Ahamed Ayoobkhan, Eswaran Chikkannan, Kannan Ramakrishnan, Saravana Balaji Balasubramanian
Publikováno v:
Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB) ISBN: 9783030006648
In this paper, a lossless image compression technique using prediction errors is proposed. To achieve better compression performance, a novel classifier which makes use of wavelet and Fourier descriptor features is employed. Artificial neural network
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6914c10aae33984affc22acb2ad02358
https://doi.org/10.1007/978-3-030-00665-5_161
https://doi.org/10.1007/978-3-030-00665-5_161