Zobrazeno 1 - 10
of 1 860
pro vyhledávání: '"Prasanna S."'
Autor:
Makrand A. Rakshe, Prasanna S. Gandhi
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)
Abstract Mimicking nature using artificial technologies has always been a quest/fascination of scientists and researchers of all eras. This paper characterizes viscous fingering instability-based, lithography-less, spontaneous, and scalable process t
Externí odkaz:
https://doaj.org/article/a140aa9b749e42d2929e5557ff3125ac
Autor:
Amit Umesh Paschapur, A. R. N. S. Subbanna, Ashish Kumar Singh, B. Jeevan, Johnson Stanley, H. Rajashekara, Krishna Kant Mishra, Prasanna S. Koti, Lakshmi Kant, Arunava Pattanayak
Publikováno v:
Egyptian Journal of Biological Pest Control, Vol 32, Iss 1, Pp 1-15 (2022)
Abstract Background The inadvertent observation of a substantial population reduction of greenhouse whiteflies infecting Salvia divinorum plants grown in a polyhouse sparked a flurry of inquiries on the cause of the population decline. The entomopath
Externí odkaz:
https://doaj.org/article/5b9b6348dffe4a6cbc1eb439482c4e0d
Autor:
Phool Singh Hindoriya, Rakesh Kumar, Rajesh Kumar Meena, Hardev Ram, Ashwani Kumar, Suryakanta Kashyap, Bisworanjita Biswal, Kanika Bhakuni, Prasanna S. Pyati, Kamal Garg, Simran Jasht, Ghous Ali, Birbal, Subhradip Bhattacharjee
Publikováno v:
Agronomy, Vol 14, Iss 2, p 339 (2024)
The importance of selecting an appropriate berseem variety and implementing effective nutrient management practices is crucial for maximizing both the production and economic potential of forage crops. This was clearly demonstrated in a field experim
Externí odkaz:
https://doaj.org/article/af48158481a14e678570876b3a858c5f
Publikováno v:
BMC Medical Research Methodology, Vol 22, Iss 1, Pp 1-10 (2022)
Abstract Background Longitudinal studies are important to understand patterns of growth in children and limited in India. It is important to identify an approach for characterising growth trajectories to distinguish between children who have healthy
Externí odkaz:
https://doaj.org/article/e7757bd5292e4990892866c81f0f9fb1
In the domain of Extended Reality (XR), particularly Virtual Reality (VR), extensive research has been devoted to harnessing this transformative technology in various real-world applications. However, a critical challenge that must be addressed befor
Externí odkaz:
http://arxiv.org/abs/2411.10489
The current work explores long-term speech rhythm variations to classify Mising and Assamese, two low-resourced languages from Assam, Northeast India. We study the temporal information of speech rhythm embedded in low-frequency (LF) spectrograms deri
Externí odkaz:
http://arxiv.org/abs/2410.20095
This paper reports a preliminary study on quantitative frequency domain rhythm cues for classifying five Indian languages: Bengali, Kannada, Malayalam, Marathi, and Tamil. We employ rhythm formant (R-formants) analysis, a technique introduced by Gibb
Externí odkaz:
http://arxiv.org/abs/2410.05724
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Abstract Is it possible to ‘explore’ metal’s intrinsic property—a cohesive interaction—which naturally transform M0 into an aggregate or a particle or film for driving oxidative C–C bond formation? With this intention, reduction of [Ag(NH
Externí odkaz:
https://doaj.org/article/8f5fa6ef13de459492a53abcf3fc5814
Autor:
Phukan, Orchid Chetia, Girish, Akhtar, Mohd Mujtaba, Behera, Swarup Ranjan, Choudhury, Nitin, Buduru, Arun Balaji, Sharma, Rajesh, Prasanna, S. R Mahadeva
The adaptation of foundation models has significantly advanced environmental audio deepfake detection (EADD), a rapidly growing area of research. These models are typically fine-tuned or utilized in their frozen states for downstream tasks. However,
Externí odkaz:
http://arxiv.org/abs/2409.15767
Autor:
Phukan, Orchid Chetia, Behera, Swarup Ranjan, Singh, Shubham, Singh, Muskaan, Rajan, Vandana, Buduru, Arun Balaji, Sharma, Rajesh, Prasanna, S. R. Mahadeva
In this study, we address the challenge of depression detection from speech, focusing on the potential of non-semantic features (NSFs) to capture subtle markers of depression. While prior research has leveraged various features for this task, NSFs-ex
Externí odkaz:
http://arxiv.org/abs/2409.14312