Zobrazeno 1 - 10
of 259
pro vyhledávání: '"Anand Rangarajan"'
MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring
Autor:
Qian Gong, Jieyang Chen, Ben Whitney, Xin Liang, Viktor Reshniak, Tania Banerjee, Jaemoon Lee, Anand Rangarajan, Lipeng Wan, Nicolas Vidal, Qing Liu, Ana Gainaru, Norbert Podhorszki, Richard Archibald, Sanjay Ranka, Scott Klasky
Publikováno v:
SoftwareX, Vol 24, Iss , Pp 101590- (2023)
We describe MGARD, a software providing MultiGrid Adaptive Reduction for floating-point scientific data on structured and unstructured grids. With exceptional data compression capability and precise error control, MGARD addresses a wide range of requ
Externí odkaz:
https://doaj.org/article/e7ccffb856204f6982e53466473b0e3c
Publikováno v:
Vehicles, Vol 4, Iss 4, Pp 1288-1313 (2022)
Road safety has always been a crucial priority for municipalities, as vehicle accidents claim lives every day. Recent rapid improvements in video collection and processing technologies enable traffic researchers to identify and alleviate potentially
Externí odkaz:
https://doaj.org/article/219c002b9e624979a475c62d81acfd85
Autor:
Jaemoon Lee, Qian Gong, Jong Choi, Tania Banerjee, Scott Klasky, Sanjay Ranka, Anand Rangarajan
Publikováno v:
Applied Sciences, Vol 12, Iss 13, p 6718 (2022)
Scientific applications continue to grow and produce extremely large amounts of data, which require efficient compression algorithms for long-term storage. Compression errors in scientific applications can have a deleterious impact on downstream proc
Externí odkaz:
https://doaj.org/article/0d896854ba8e4812a9c2b54fdacca252
Publikováno v:
Journal of Imaging, Vol 8, Iss 4, p 101 (2022)
Travel-time estimation of traffic flow is an important problem with critical implications for traffic congestion analysis. We developed techniques for using intersection videos to identify vehicle trajectories across multiple cameras and analyze corr
Externí odkaz:
https://doaj.org/article/8219b44db2ad48e49491b9b92323e7a9
Publikováno v:
Applied Sciences, Vol 12, Iss 4, p 2075 (2022)
In this paper, we propose a novel approach to commodity classification from surveillance videos by utilizing logo data on trucks. Broadly, most logos can be classified as predominantly text or predominantly images. For the former, we leverage state-o
Externí odkaz:
https://doaj.org/article/69d2eed481a645e49f0efd5bfb35ce07
Publikováno v:
PLoS ONE, Vol 15, Iss 3, p e0229774 (2020)
As demands on agriculture increase, food producers will need to employ management strategies that not only increase yields but reduce environmental impacts. Modeling is a powerful tool for informing decision-making about current and future practices.
Externí odkaz:
https://doaj.org/article/e000d63f7251423fb872a5f3e9936ec6
Publikováno v:
Remote Sensing, Vol 13, Iss 22, p 4605 (2021)
Advanced machine learning techniques have been used in remote sensing (RS) applications such as crop mapping and yield prediction, but remain under-utilized for tracking crop progress. In this study, we demonstrate the use of agronomic knowledge of c
Externí odkaz:
https://doaj.org/article/8537054293da40fd830ceb330f6817a0
Publikováno v:
Entropy, Vol 20, Iss 8, p 575 (2018)
We consider the problem of model selection using the Minimum Description Length (MDL) criterion for distributions with parameters on the hypersphere. Model selection algorithms aim to find a compromise between goodness of fit and model complexity. Va
Externí odkaz:
https://doaj.org/article/4b214aa7abb44cd7bb4fd2b9b1152f52
Publikováno v:
Agronomy Journal. 115:1214-1236
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:861-869
In this paper, we present a new self-supervised scene flow estimation approach for a pair of consecutive point clouds. The key idea of our approach is to represent discrete point clouds as continuous probability density functions using Gaussian mixtu