Signal representation for compression and noise reduction through frame-based wavelets

Published versio

Theoretical Marxist approaches in palaeodemography aspects of three Greek regions

The question of the nature of human activity, its specific formulation and function in social production and reproduction is a fundamental one for any theory of social formation, existence and evolution. There are various forces to accounts for which do not remain static as they are categories of human needs and consciousness and they are transformed as society changes. Nonetheless theoretical pre-suppositions in general have rested on the validity of rigid argumentations embedded in a tradition of conservative ideology, with their central feature the a priori reduction of population dynamics and social values to eternal natural laws. In this "Hobbesian society" concepts, categories and methods are the products of the very phenomena they are designed to describe; the effect is empirical closure, artificial separation of the object from its history, and the application in any field of the "true or false” hypotheses, which once categorized remain ever so. However, an understanding of the reality depends on the question we ask. Rather than seeking comparabilities in statistical terms and countings according to some unstated value scheme considered as proven, the Marxist commitment is to detailed study of societies, with written or non-written history, based on the dialectical-historical analysis of relationships and contradictions that must be elaborated, refined and tested both through theory and praxis; and this is the concern of the following thesis

A digital signal processing perspective on a stability test of linear system transfer functions

Published versio

Dynamic Knowledge Distillation with A Single Stream Structure for RGB-D Salient Object Detection

RGB-D salient object detection(SOD) demonstrates its superiority on detecting in complex environments due to the additional depth information introduced in the data. Inevitably, an independent stream is introduced to extract features from depth images, leading to extra computation and parameters. This methodology which sacrifices the model size to improve the detection accuracy may impede the practical application of SOD problems. To tackle this dilemma, we propose a dynamic distillation method along with a lightweight framework, which significantly reduces the parameters. This method considers the factors of both teacher and student performance within the training stage and dynamically assigns the distillation weight instead of applying a fixed weight on the student model. Extensive experiments are conducted on five public datasets to demonstrate that our method can achieve competitive performance compared to 10 prior methods through a 78.2MB lightweight structure

Smooth signal extraction from instantaneous mixtures

Published versio

FFT-based estimation of large motions in images: a robust gradient-based approach

A fast and robust gradient-based motion estimation technique which operates in the frequency domain is presented. The algorithm combines the natural advantages of a good feature selection offered by gradient-based methods with the robustness and speed provided by FFT-based correlation schemes. Experimentation with real images taken from a popular database showed that, unlike any other Fourier-based techniques, the method was able to estimate translations, arbitrary rotations and scale factors in the range 4-6

FFT-based estimation of large motions in images: a robust gradient-based approach

A fast and robust gradient-based motion estimation technique which operates in the frequency domain is presented. The algorithm combines the natural advantages of a good feature selection offered by gradient-based methods with the robustness and speed provided by FFT-based correlation schemes. Experimentation with real images taken from a popular database showed that, unlike any other Fourier-based techniques, the method was able to estimate translations, arbitrary rotations and scale factors in the range 4-6