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9 results on '"BHATT, RISHABH"'

3. Introducing time parallelisation within data assimilation using parareal method

Author

Bhatt, Rishabh, Debreu, Laurent, Vidard, Arthur, Mathematics and computing applied to oceanic and atmospheric flows (AIRSEA), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Grenoble Alpes (UGA)-Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), and ANR-18-CE46-0008,ADOM,Méthodes de décomposition de domaine asynchrones(2018)

Subjects
Numerical Analysis, Parareal, High Performance Computing, Optimisation, Variational Data Assimilation, Krylov Subspace Methods, Computer Science::Numerical Analysis, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Mathematics::Numerical Analysis
Abstract

Forecasts made by 4-D Var involves forward integration of model before proceeding for the minimisation process. While one reaches saturation in space parallelisation we try to obtain some speedup by integrating our model using the Parareal method. Our setting ensures that the minimum is obtained by solving a linear symmetric system. We use a modified version of the inexact conjugate gradient method where the matrix-vector multiplication is supplied by the parareal. This helps us to determine a specific stopping criterion for the parareal. The results are demonstrated by considering a 1-D linear shallow water model. Our method produces a speedup factor of 3 using fewer parareal iterations as compared to the same results obtained by the exact conjugate gradient method.

Published
2022

6. Indian Sign Recognition System using Adaptable Segmentation and Machine Learning.

Author

Bhatt, Rishabh and Bharti, Vishal

Subjects
MACHINE learning, SIGN language, IMAGE recognition (Computer vision), COMMUNICATION barriers
Abstract

Deaf community all over the world uses sign language as a means of communication. Although it resolves the communication barrier among the community itself, the integration of acoustic and sign language is still matter of research. This paper proposes a dynamically adaptable image recognition module coupled with convolution neural network to recognize hand signs. The paper addresses the problem of isolation of hand from a robust environment and recognizing the hand sign. A series of transformation and segmentation is applied to the input, which in turns helps in feature extraction. Preprocessing of both training and input and is done to give a performance boost. Comparative study is drawn in the end to find the effect of pre-processing, of input and training data, on the classification speed. [ABSTRACT FROM AUTHOR]

Published
2020

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