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A data driven method for feature transformation
2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012Most image understanding algorithms begin with the extraction of information thought to be relevant to the particular task. This is commonly known as feature extraction and has, up to this date, been a largely manual process, where a reasonable method is chosen through validation on the experimented dataset. In this work we propose a data driven, local
Mert Dikmen +2 more
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On the Data-Driven Generalized Cell Mapping Method
International Journal of Bifurcation and Chaos, 2019Global analysis is often necessary for exploiting various applications or understanding the mechanisms of many dynamical phenomena in engineering practice where the underlying system model is too complex to analyze or even unavailable. Without a mathematical model, however, it is very difficult to apply cell mapping for global analysis. This paper for
Zigang Li +3 more
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A Comparison of Data-Driven Automatic Syllabification Methods
2009Although automatic syllabification is an important component in several natural language tasks, little has been done to compare the results of data-driven methods on a wide range of languages. This article compares the results of five data-driven syllabification algorithms (Hidden Markov Support Vector Machines, IB1, Liang's algorithm, the Look Up ...
Connie R. Adsett, Yannick Marchand
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A Data-driven Method for Competency Evaluation of Personnel
Proceedings of the 3rd International Conference on Data Science and Information Technology, 2020Nowadays, human capital is very important for organizations. The organizations with more outstanding talents can often gain a foothold in the fierce competition. As a tool to measure talents' performance, competency model often plays a vital role in identifying and evaluating talents.
Jiting Li +4 more
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Data‐driven projection method in fluid simulation
Computer Animation and Virtual Worlds, 2016AbstractPhysically based fluid simulation requires much time in numerical calculation to solve Navier–Stokes equations. Especially in grid‐based fluid simulation, because of iterative computation, the projection step is much more time‐consuming than other steps.
Cheng Yang, Xubo Yang, Xiangyun Xiao
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Recommending electricity plans: A data-driven method
2016 IEEE International Conference on Smart Grid Communications (SmartGridComm), 2016In this paper, a customized electricity retailing plan recommendation strategy is developed. Cost-effective retailing plans are recommended according to customer's electricity usage pattern. Usage pattern is recognized through classifying daily load profile (DLP) into a certain class, which is obtained in DLP clustering process.
Yuan Zhang 0011 +4 more
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Data Driven Statistical Methods
Technometrics, 2000A. Dale Magoun, Peter Sprent
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Data-Driven Inverse Design Method for Turbomachinery
Volume 12D: Turbomachinery — Multidisciplinary Design Approaches, Optimization, and Uncertainty Quantification; Radial Turbomachinery Aerodynamics; Unsteady Flows in TurbomachineryAbstract A data-driven inverse design method based on neural networks is proposed for turbomachinery. In the devised methodology, design parameters are provided as input to the neural network, and performance attributes, e.g. efficiency, as output. Once trained, the network is used for inverse design, i.e.
So, Kwok Kai +3 more
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Data-driven methods in Rheology
Rheologica Acta, 2023Kyung Hyun Ahn, Safa Jamali
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