Results 121 to 130 of about 1,704,825 (163)

Full-Reference and No-Reference Objective Evaluation of Deep Neural Network Speech

2021 13th International Conference on Quality of Multimedia Experience (QoMEX), 2021
Objective speech quality and intelligibility estimators do not correctly assess speech generated by deep neural networks (DNNs). We use 256 speech files and subjective scores that cover 14 DNN speech conditions and 18 nonDNN speech conditions to show that 8 different full-reference (FR) estimators consistently underestimate subjective scores for the ...
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Full-Blooded Reference

Philosophia Mathematica, 2007
In ‘Just what is full-blooded platonism?’ Greg Restall outlines several objections to Mark Balaguer's theory of full-blooded platonism. I reply to these objections by explicating the semantic framework for the reference of mathematical terms that full-blooded platonism requires.
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Full-reference quality diagnosis for video summary

2008 IEEE International Conference on Multimedia and Expo, 2008
As video summarization techniques have attracted more and more attention for efficient multimedia data management, objective quality assessment of video summary is desired. To address the lack of automatic evaluation techniques, this paper proposes a 3C-diagnosis algorithm to diagnose the video summary from the perspective of coverage, conciseness, and
Yan Liu 0004, Yan Zhang 0031, Maosong Sun 0001, Wenjie Li 0002   +3 more
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Full-Reference Quality Assessment for Video Summary

2008 IEEE International Conference on Data Mining Workshops, 2008
As video summarization techniques have attracted more and more attention for efficient multimedia data management, quality assessment of video summary is required. To address the lack of automatic evaluation techniques, this paper proposes a novel framework including several new algorithms to assess the quality of the video summary against a given ...
Tongwei Ren, Yan Liu 0004, Gangshan Wu
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Image quality evaluation of full reference algorithm

MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 2018
Image quality evaluation is a classic research topic, the goal is to design the algorithm, given the subjective feelings consistent with the evaluation value. This paper mainly introduces several typical reference methods of Mean Squared Error(MSE), Peak Signal to Noise Rate(PSNR), Structural Similarity Image Metric(SSIM) and feature similarity(FSIM ...
Nannan He, Kai Xie, Tong Li, Yushan Ye
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Full-Reference Metric Adaptive Image Denoising

2019 IEEE International Conference on Image Processing (ICIP), 2019
The performance of image denoising algorithms generally depends largely on the selection of the parameters. We address the problem of optimizing the denoising parameters to achieve maximum denoising performance. Most existing methods for no-reference denoising parameter optimization either use the estimated image noise or individual no-reference image ...
Kenji Hara, Kohei Inoue, Kiichi Urahama
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A Full-Reference Quality Metric for Geometrically Distorted Images

IEEE Transactions on Image Processing, 2010
In multimedia applications, there has been an increasing interest in the use of quality measures based on human perception; however, research has not dealt with distortions due to geometric transformations. In this paper, we propose a method to objectively assess the perceptual quality of geometrically distorted images, based on image features ...
D'ANGELO, A., ZHAOPING, L., BARNI, M.
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Disparity weighting applied to full-reference and no reference stereoscopic image quality assessment

2015 IEEE International Conference on Consumer Electronics (ICCE), 2015
This paper presents an evaluation of performance of the disparity weighting technique when it is applied to stereoscopic image quality assessment in full reference and no-reference scenarios. The correlation coefficients between the subjective scores in the LIVE 3D Database and the predicted scores indicate a significant increase in the performance.
José Vinícius de Miranda Cardoso, Carlos Danilo Miranda Regis, Marcelo Sampaio de Alencar   +2 more
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Full Reference Image Quality Assessment: Limitation

2014 22nd International Conference on Pattern Recognition, 2014
In this work, we propose to study the universality of the Full-Reference Image Quality metrics (FR-IQMs) and show the no-relevance to use this kind of metrics without considering the degradation type contained in the image. Different experimental tests have been done in order to analyze its performance.
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Full-Reference Methods and Machine Learning

2018
This chapter introduces the application of machine learning to Image Quality Assessment (IQA) in the case of computer-generated images. The classical learning machines, like SVMs, are quickly remained and RVMs are presented to deal with this particular IQA case (noise features learning).
André Bigand, Julien Dehos, Christophe Renaud, Joseph Constantin   +3 more
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