Results 181 to 190 of about 6,879 (215)

DOD-Boost: a temporal and distribution-optimized deep boosting framework for solar radiation modeling. [PDF]

Sci Rep
Mert İ.
europepmc   +1 more source

Equivalence of Informations Characterizes Bregman Divergences. [PDF]

Entropy (Basel)
Chodrow PS.
europepmc   +1 more source

Analysis of symbolic sequences using the Jensen-Shannon divergence

Physical Review E, 2002
We study statistical properties of the Jensen-Shannon divergence D, which quantifies the difference between probability distributions, and which has been widely applied to analyses of symbolic sequences. We present three interpretations of D in the framework of statistical physics, information theory, and mathematical statistics, and obtain ...
Grosse, Ivo, Bernaola-Galván, Pedro, Carpena, Pedro, Román-Roldán, Ramón, Oliver, Jose, Stanley, H. Eugene   +5 more
openaire   +3 more sources

On the Equivalence Between Jensen–Shannon Divergence and Michelson Contrast

IEEE Transactions on Information Theory, 2012
This paper focuses on the link between a visible linear and local distortion in a pictorial scene and its cost in terms of information theory quantities. In particular, a formal relation between the Michelson visual contrast and the Jensen-Shannon divergence (JSD) will be provided. A universal just noticeable threshold is also derived by maximizing JSD
BRUNI, VITTORIA, Elisa Rossi, Domenico Vitulano   +2 more
openaire   +4 more sources

Jensen Shannon Divergence as Reduced Reference Measure for Image Denoising

, 2016
This paper focuses on the use the Jensen Shannon divergence for guiding denoising. In particular, it aims at detecting those image regions where noise is masked; denoising is then inhibited where it is useless from the visual point of view. To this aim a reduced reference version of the Jensen Shannon divergence is introduced and it is used for ...
Bruni V, Vitulano D
openaire   +2 more sources

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Permutation Jensen–Shannon divergence for Random Permutation Set

Engineering Applications of Artificial Intelligence, 2023
Yong Deng, Kang Hao Cheong
exaly   +2 more sources

Generalized quantum Jensen-Shannon divergence of imaginarity

Physics Letters, Section A: General, Atomic and Solid State Physics
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yuan Sun
exaly   +3 more sources

Enhanced mass Jensen–Shannon divergence for information fusion

Expert Systems With Applications, 2022
Lipeng Pan, Xiaozhuan Gao, Yong Deng
exaly   +2 more sources

The Jensen-Shannon divergence

Journal of the Franklin Institute, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Menéndez, M. L., Pardo, J. A., Pardo, L., Pardo, M. C.   +3 more
openaire   +2 more sources

Dilation of Chisini-Jensen-Shannon Divergence

2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2016
Jensen-Shannon divergence (JSD) does not provide adequate separation when the difference between input distributions is subtle. A recently introduced technique, Chisini Jensen Shannon Divergence (CJSD), increases JSD's ability to discriminate between probability distributions by reformulating with operators from Chisini mean.
Piyush Kumar Sharma, Gary Holness
openaire   +1 more source