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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.

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Multiplicative Update Rules for Concurrent Nonnegative Matrix Factorization and Maximum Margin Classification

TL;DR: Experimental results in several databases indicate that the incorporation of the maximum margin classification constraints into the NMF and discriminant NMF objective functions improves the accuracy of the classification.
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Projection distortion analysis for flattened image mosaicing from straight uniform generalized cylinders

TL;DR: This paper presents a new approach for reconstructing images mapped or painted on straight uniform generalized cylinders (SUGC), and evaluates the lower and the upper bounds of the necessary number of views in order to represent the entire scene from a SUGC by considering the distortions produced by perspective projection.
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A new methodology for the comparative study of the root canal instrumentation techniques based on digital radiographic image processing and analysis

TL;DR: Evaluating the utility of digital image processing and analysis procedures for the study and comparison of the efficiency of 2 root canal instrumentation techniques provided the ability to visualize dentin lost during root canalstrumentation, compare root canal morphology before and after instrumentation, and quantitatively evaluate the enlargement of the root canal area induced by each of the instrumentations.
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UAV Cinematography Constraints Imposed by Visual Target Tracking

TL;DR: This paper focuses on formalizing and geometrically modelling common target-following UAV motion types, in order to analytically determine the maximum permissible camera focal length (therefore, the range of feasible shot types) for avoiding visual target tracking failure.
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Entropy metrics used for video summarization

TL;DR: The method for shot cut detection relies on the mutual information and the joint entropy between the frames and it is demonstrated that the method detects both fades and abrupt cuts with high accuracy.