Low-discrepancy Sampling for Full Reference Image Quality Assessment Speed Up-Reference-Cited by-同舟云学术

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Low-discrepancy Sampling for Full Reference Image Quality Assessment Speed Up

Published:2022-07-18 Issue: Volume: Page:
ISSN:
Container-title:2022 International Joint Conference on Neural Networks (IJCNN)
language:
Short-container-title:

Author:

Galvao Jair¹,Ren Tsang Ing²,Madeiro Francisco³,Lima Emerson A. O.³

Affiliation:

1. Centro de Informática (CIN), Universidade Federal de Pernambuco (UFPE) and Instituto Federal de Pernambuco (IFPE),Recife,Brazil

2. Centro de Informática (CIN), Universidade Federal de Pernambuco (UFPE),Recife,Brazil

3. Polytechnic School of Pernambuco (POLI), University of Pernambuco (UPE),Recife,Brazil

Funder

Brazilian National Council for Scientific and Technological Development (CNPq)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9891857/9889787/09891972.pdf?arnumber=9891972

Reference36 articles.

1. On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals

2. The discrepancy of generalized Van-der-Corput–Halton sequences

3. Algorithm 659

4. Sequências de baixa discrepância aplicadas àvaliacao de qualidade de imagens comprimidas;lima;TEMA Trend Mat Apl Comput,2009

5. On the distribution of points in a cube and the approximate evaluation of integrals

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