Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Meenakshi Kollati"'
Publikováno v:
Cogent Engineering, Vol 11, Iss 1 (2024)
This article proposes a video watermarking technique by concealing the watermark in the low frequency bands of phase using Conjugate Symmetric Sequency Complex Hadamard Transform (CS-SCHT) and Speeded Up Robust Feature (SURF). The CS-SCHT is effectiv
Externí odkaz:
https://doaj.org/article/ffdbb042beb34f859e24cbc3871844e8
Autor:
Yasasvy Tadepalli, Meenakshi Kollati, Swaraja Kuraparthi, Padmavathi Kora, Anil Kumar Budati, Lakshmi Kala Pampana
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 6, Iss 2, Pp 135-146 (2021)
Abstract Rapid growth in the transfer of multimedia information over the Internet requires algorithms to retrieve a queried image from large image database repositories. The proposed content‐based image retrieval (CBIR) uses Gaussian–Hermite mome
Externí odkaz:
https://doaj.org/article/20b5a29a4e424a1998a2857938ca795c
Publikováno v:
Traitement du Signal. 38:1485-1493
Monocular depth estimation is a hot research topic in autonomous car driving. Deep convolution neural networks (DCNN) comprising encoder and decoder with transfer learning are exploited in the proposed work for monocular depth map estimation of two-d
Autor:
Swaraja Kuraparthi, Padmavathi Kora, Meenakshi Kollati, Hima Bindu Valiveti, V. Sravan, Chaitanya Duggineni, Madhavi K. Reddy, C.N. Sujatha
Publikováno v:
Traitement du Signal. 38:1171-1179
Manual tumor diagnosis from magnetic resonance images (MRIs) is a time-consuming procedure that may lead to human errors and may lead to false detection and classification of the tumor type. Therefore, to automatize the complex medical processes, a d
Autor:
Padmavathi Kora, Anil Kumar Budati, Lakshmi Kala Pampana, Swaraja Kuraparthi, Yasasvy Tadepalli, Meenakshi Kollati
Publikováno v:
CAAI Transactions on Intelligence Technology, Vol 6, Iss 2, Pp 135-146 (2021)
Rapid growth in the transfer of multimedia information over the Internet requires algorithms to retrieve a queried image from large image database repositories. The proposed content‐based image retrieval (CBIR) uses Gaussian–Hermite moments as th
Publikováno v:
Traitement du Signal. 36:565-573