The channel representation allows the construction of soft histograms, where peaks can be detected with a much higher accuracy than in regular hard-binned ...
Oct 11, 2009 · The channel representation allows the construction of soft histograms, where peaks can be detected with a much higher accuracy than in regular ...
The main focus of this paper is on how to reconstruct p from the channel coefficients cn . Reconstruction of Probability Density Functions 3 493 Maximum Entropy ...
Reconstruction of Probability Density Functions from Channel Representations ... Forssén, P.-E.: Low and Medium Level Vision using Channel Representations.
A technique is presented for representing linear features as probability density functions in two or three dimen- sions. Three chief advantages of this ...
Missing: Channel | Show results with:Channel
A method of obtaining the probability density function (PDF) of local properties from path integrated measurements is described.
Missing: Channel Representations.
May 17, 2024 · Here, we ask participants to indicate what they perceive in images made of random visual features in a deep neural network.
The proposed construction provides a method for recovery of different pdfs via simple transformations of the moment sequences. Uniform and L1-rates of ...
The projection of sample measurements onto a reconstruction space represented by a basis on a regular grid is a powerful and simple approach to estimate a ...
... distribution. The proposed framework is incorporated into the so called channel representation, which can be interpreted as discrete PDFs under certain ...