Zobrazeno 1 - 10 of 96 pro vyhledávání: '"T. Rajamani"'
1
Akademický článek
Computational insight into the spectroscopic and molecular docking analysis of estrogen receptor with ligand 2,3-dimethyl-N[2-(hydroxy)benzylidene] aniline
Autor: A. Prabakaran, C. Uma Maheswari, Noureddine ISSAOUI, Omar M. Al-Dossary, T. Rajamani, T. Gnanasambandan, P. Saravanan, M. Vimalan, A. Manikandan
Publikováno v: Journal of King Saud University: Science, Vol 36, Iss 6, Pp 103196- (2024)
A comprehensive approach encompassing a blend of spectral techniques and Density Functional Theory (DFT) was employed to elucidate the electronic, vibrational, structural, and nonlinear optical properties of 2,3-dimethyl-N[2-(Hydroxy)benzylidene] ani
Externí odkaz: https://doaj.org/article/4c1aba9f73e84876b0a5e790f209a4cd
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2
Attention-augmented U-Net (AA-U-Net) for semantic segmentation
Autor: Kumar T. Rajamani, Priya Rani, Hanna Siebert, Rajkumar ElagiriRamalingam, Mattias P. Heinrich
Publikováno v: Signal, Image and Video Processing. 17:981-989
Deep learning-based image segmentation models rely strongly on capturing sufficient spatial context without requiring complex models that are hard to train with limited labeled data. For COVID-19 infection segmentation on CT images, training data are
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::335ec08d0d2e0d365c0de4cc5161d0ac
https://doi.org/10.1007/s11760-022-02302-3
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3
Akademický článek
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6
Classification of Low-Grade and High-Grade Glioma from MR Brain Images Using Multiple-Instance Learning with Combined Feature Set
Autor: V L Lajish, Kumar T. Rajamani, C. C. Benson
Publikováno v: Vietnam Journal of Computer Science. :163-186
Fully automatic brain image classification of MR brain images is of great importance for research and clinical studies, since the precise detection may lead to a better treatment. In this work, an efficient method based on Multiple-Instance Learning
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::649793b92a1562d7e191d51f4ccef3cc
https://doi.org/10.1142/s2196888822500117
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7
Akademický článek
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9
A Novel Attention-Based Gated Recurrent Unit and its Efficacy in Speech Emotion Recognition
Autor: Kumar T. Rajamani, Srividya Tirunellai Rajamani, Shuo Liu, Björn Schuller, Adria Mallol-Ragolta
Publikováno v: ICASSP
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Notwithstanding the significant advancements in the field of deep learning, the basic long short-term memory (LSTM) or Gated Recurrent Unit (GRU) units have largely remained unchanged and unexplored. There are several possibilities in advancing the s
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::abc928f0bf0eac4eaa5e29d22c1a9736
https://doi.org/10.1109/icassp39728.2021.9414489
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