Zobrazeno 1 - 10
of 32 807
pro vyhledávání: '"Raghavendra AS"'
Recommendations for improved tropical cyclone formation and position probabilistic Forecast products
Autor:
Jason P. Dunion, Chris Davis, Helen Titley, Helen Greatrex, Munehiko Yamaguchi, John Methven, Raghavendra Ashrit, Zhuo Wang, Hui Yu, Anne-Claire Fontan, Alan Brammer, Matthew Kucas, Matthew Ford, Philippe Papin, Fernando Prates, Carla Mooney, Andrew Kruczkiewicz, Paromita Chakraborty, Andrew Burton, Mark DeMaria, Ryan Torn, Jonathan L. Vigh
Publikováno v:
Tropical Cyclone Research and Review, Vol 12, Iss 4, Pp 241-258 (2023)
Prediction of the potentially devastating impact of landfalling tropical cyclones (TCs) relies substantially on numerical prediction systems. Due to the limited predictability of TCs and the need to express forecast confidence and possible scenarios,
Externí odkaz:
https://doaj.org/article/6db7bb53613a40869deddb5e5113a85e
Publikováno v:
Meteorological Applications, Vol 30, Iss 4, Pp n/a-n/a (2023)
Abstract We assess the skill of the fully coupled lagged ensemble forecasts from GloSea5‐GC2, for the sub‐seasonal to seasonal (S2S) timescale up to 4 weeks, with the aim of understanding how these forecasts might be used in a Ready‐Set‐Go st
Externí odkaz:
https://doaj.org/article/9498456936fd40dabab329824059f60e
Autor:
Rao, P Raghavendra, Vyavahare, Pooja
This work studies the distributed learning process on a network of agents. Agents make partial observation about an unknown hypothesis and iteratively share their beliefs over a set of possible hypotheses with their neighbors to learn the true hypoth
Externí odkaz:
http://arxiv.org/abs/2411.11411
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
Autor:
Sharma, Geetanjali, Tandon, Abhishek, Jaswal, Gaurav, Nigam, Aditya, Ramachandra, Raghavendra
Iris recognition technology plays a critical role in biometric identification systems, but their performance can be affected by variations in iris pigmentation. In this work, we investigate the impact of iris pigmentation on the efficacy of biometric
Externí odkaz:
http://arxiv.org/abs/2411.08490
This study sought to better understand the causes of price disparity in cesarean sections, using newly released hospital data. Beginning January 1, 2021, Centers for Medicare and Medicaid Services (CMS) requires hospitals functioning in the United St
Externí odkaz:
http://arxiv.org/abs/2411.08174
Autor:
Sayana, Krishna, Vasudeva, Raghavendra, Vasilevski, Yuri, Su, Kun, Hebert, Liam, Pham, Hubert, Jash, Ambarish, Sodhi, Sukhdeep
The recent advances in Large Language Model's generation and reasoning capabilities present an opportunity to develop truly conversational recommendation systems. However, effectively integrating recommender system knowledge into LLMs for natural lan
Externí odkaz:
http://arxiv.org/abs/2410.16780
Autor:
Vasudevan, Ekamresh, Sridhara, Shashank N., Pavez, Eduardo, Ortega, Antonio, Singh, Raghavendra, Kalluri, Srinath
We present a novel method to correct flying pixels within data captured by Time-of-flight (ToF) sensors. Flying pixel (FP) artifacts occur when signals from foreground and background objects reach the same sensor pixel, leading to a confident yet inc
Externí odkaz:
http://arxiv.org/abs/2410.08084
Autor:
PN, Aravinda Reddy, Ramachandra, Raghavendra, Venkatesh, Sushma, Rao, Krothapalli Sreenivasa, Mitra, Pabitra, Krishna, Rakesh
Face recognition systems (FRS) can be compromised by face morphing attacks, which blend textural and geometric information from multiple facial images. The rapid evolution of generative AI, especially Generative Adversarial Networks (GAN) or Diffusio
Externí odkaz:
http://arxiv.org/abs/2410.07625
Autor:
Tripathi, Raghavendra
In a seminal paper in 1959, Marcus and Ree proved that every $n\times n$ bistochastic matrix $A$ satisfies $\|A\|_{F}^2\leq \max_{\sigma\in S_n}A_{i,\sigma(i)}$ where $S_n$ is the symmetric group on $\{1, \ldots, n\}$. Erd\H{o}s asked to characterize
Externí odkaz:
http://arxiv.org/abs/2410.06612