Impulsive Noise Suppression from Highly Corrupted Images by Using Resilient Neural Networks - researchr publication related

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Erkan Besdok, Pinar Çivicioglu, Mustafa Alçi. Impulsive Noise Suppression from Highly Corrupted Images by Using Resilient Neural Networks. In Leszek Rutkowski, Jörg H. Siekmann, Ryszard Tadeusiewicz, Lotfi A. Zadeh, editors, Artificial Intelligence and Soft Computing - ICAISC 2004, 7th International Conference, Zakopane, Poland, June 7-11, 2004, Proceedings. Volume 3070 of Lecture Notes in Computer Science, pages 670-675, Springer, 2004. [doi]

The following publications are possibly variants of this publication:

Using LM Artificial Neural Networks and eta-Closest-Pixels for Impulsive Noise Suppression from Highly Corrupted ImagesPinar Çivicioglu. isnn 2005: 679-684 [doi]

Using an Exact Radial Basis Function Artificial Neural Network for Impulsive Noise Suppression from Highly Distorted Image DatabasesPinar Çivicioglu, Mustafa Alçi, Erkan Besdok. advis 2004: 383-391 [doi]

Using a Neuro-Fuzzy Network for Impulsive Noise Suppression from Highly Distorted Images of WEB-TVsPinar Çivicioglu. awic 2005: 107-113 [doi]

A new method for impulsive noise suppression from highly distorted images by using AnfisErkan Besdok. eaai, 17(5):519-527, 2004. [doi]

Using an adaptive neuro-fuzzy inference system-based interpolant for impulsive noise suppression from highly distorted imagesErkan Besdok, Pinar Çivicioglu, Mustafa Alçi. fss, 150(3):525-543, 2005. [doi]

Impulsive Noise Suppression from Images by Using Anfis Interpolant and LillietestErkan Besdok. ejasp, 2004(16):2423-2433, 2004. [doi]

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