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Ioannis Pitas
Researcher at Aristotle University of Thessaloniki
Publications - 826
Citations - 26338
Ioannis Pitas is an academic researcher from Aristotle University of Thessaloniki. The author has contributed to research in topics: Facial recognition system & Digital watermarking. The author has an hindex of 76, co-authored 795 publications receiving 24787 citations. Previous affiliations of Ioannis Pitas include University of Bristol & University of York.
Papers
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Journal ArticleDOI
Median radial basis function neural network
Adrian G. Bors,Ioannis Pitas +1 more
TL;DR: The median radial basis function (MRBF) algorithm is introduced based on robust estimation of the hidden unit parameters and employs the marginal median for kernel location estimation and the median of the absolute deviations for the scale parameter estimation.
Journal ArticleDOI
Image authentication techniques for surveillance applications
TL;DR: A novel algorithm which is suitable for VS visual data authentication is presented and the results obtained by applying it to test data are discussed.
Proceedings ArticleDOI
Circularly symmetric watermark embedding in 2-D DFT domain
V. Solachidis,Ioannis Pitas +1 more
TL;DR: An algorithm for rotation and scale invariant watermarking of digital images that is robust to compression, filtering, cropping, translation and rotation and does not require the original image.
Journal ArticleDOI
Blind robust watermarking schemes for copyright protection of 3D mesh objects
TL;DR: Two novel methods suitable for blind 3D mesh object watermarking applications are proposed, one of which is robust against 3D rotation, translation, and uniform scaling and the other against both geometric and mesh simplification attacks.
Journal ArticleDOI
On the kernel Extreme Learning Machine classifier
TL;DR: The connection of the kernel versions of the ELM classifier with infinite Single-hidden Layer Feedforward Neural networks is discussed and it is shown that the original ELM kernel definition can be adopted for the calculation of theELM kernel matrix for two of the most common activation functions.