This repository contains projects related to various aspects of image processing, from basic operations to advanced techniques like active contours. Examples and case studies focus on applications in medical imaging.

Source code for the evaluated benchmarks and proposed cache management technique, GRASP, in [Faldu et al., HPCA'20].

Fits a discharge rating curve based on the power-law and the generalized power-law from data on paired water elevation and discharge measurements in a given river using a Bayesian hierarchical model as described in Hrafnkelsson et al. (2022)

Library for rain estimation and detection built with PyTorch. This library provides an implementation of algorithms for extracting rain-rate using data from commercial microwave links (CMLs). Addinaly this project provide an example dataset with data from two CMLs and implementation of performance and robustness metrics

Source code for the evaluated benchmarks and proposed cache management technique, GRASP, in [Faldu et al., HPCA'20].

Source code for the graph reordering technique, DBG, published in [Faldu et al., IISWC'19].

Source code for the graph reordering technique, DBG, published in [Faldu et al., IISWC'19].

Pareto (Type I) distributed pseudorandom numbers.

Create a readable stream for generating pseudorandom numbers drawn from a Pareto (Type I) distribution.

Solves the Cauchy Momentum equations for a non-newtonian incompressible fluid using the Finite Difference Method on a 2D grid. The solver is of the explicit type with each iteration corresponding to a step forward in time. The viscosity is updated at each grid point as per the truncated power law.

Implementation of Power Law Graph Transformer for Machine Translation and Representation Learning.

Create an array containing pseudorandom numbers drawn from a Pareto (Type I) distribution.

Natural logarithm of the probability density function (PDF) for a Pareto (Type I) distribution.

A DSL for asserting password composition policy effectiveness.

Code and data repository supporting "Power-law scaling relationships link canopy structural complexity and height across forest types."

The project for the course "Web Information Retrieval"

Create an iterator for generating pseudorandom numbers drawn from a Pareto (Type I) distribution.

Pareto distribution (Type I) probability density function (PDF).

This the code of my bachelor thesis with the CG2 lab in the university of Crete.

Modified gap statistic (gap-com) for regularization selection of sparse networks. This method is aimed for complex network estimation.