Results 181 to 190 of about 719,028 (211)

Enhanced mass Jensen–Shannon divergence for information fusion

Expert Systems With Applications, 2022
Yong Deng, Lipeng Pan, Kang Hao Cheong
exaly   +3 more sources

Permutation Jensen–Shannon divergence for Random Permutation Set

Engineering Applications of Artificial Intelligence, 2023
Yong Deng, Kang Hao Cheong
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

Non-logarithmic Jensen–Shannon divergence

Physica A: Statistical Mechanics and its Applications, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lamberti, Pedro W., Majtey, Ana P.
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

An Analysis of Edge Detection by Using the Jensen-Shannon Divergence

Journal of Mathematical Imaging and Vision, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
José Martínez-Aroza, Aureliano M Robles-Pérez   +1 more
exaly   +3 more sources

Jensen–Shannon divergence for visual quality assessment

Signal, Image and Video Processing, 2013
This paper focuses on some theoretical properties of the Jensen–Shannon divergence (JSD) that well match human visual system (HVS) features. In particular, it is firstly shown that JSD between the probability density function (pdf) of the reference (original) image and the test (distorted) one can be reformulated as a mathematical expansion ...
Bruni V, Rossi E, Vitulano D
openaire   +5 more sources

Graph Kernels from the Jensen-Shannon Divergence

Journal of Mathematical Imaging and Vision, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lu Bai 0001, Edwin R. Hancock
openaire   +3 more sources

Stratified regularity measures with Jensen-Shannon divergence

2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
This paper proposes a stratified regularity measure: a novel entropic measure to describe data regularity as a function of data domain stratification. Jensen-Shannon divergence is used to compute a set-similarity of intensity distributions derived from stratified data.
Kazunori Okada, Senthil Periaswamy, Jinbo Bi   +2 more
openaire   +1 more source

Jensen-Shannon divergence and Hilbert space embedding

International Symposium onInformation Theory, 2004. ISIT 2004. Proceedings., 2004
This paper describes the Jensen-Shannon divergence (JSD) and Hilbert space embedding. With natural definitions making these considerations precise, one finds that the general Jensen-Shannon divergence related to the mixture is the minimum redundancy, which can be achieved by the observer. The set of distributions with the metric /spl radic/JSD can even
Topsøe, Flemming, Fuglede, Bent
openaire   +1 more source