Gradient Vector Flow (GVF) is a feature-preserving diffusion of gradient information. It was originally introduced by Xu and Prince to drive snakes, or active contours, towards edges of interest in image segmentation. But GVF...
While the OpenCL API is written in C, the OpenCL 1.1 specification also comes with a specification for C++ bindings. In this post I go through how to use the C++ bindings instead of...
The neural network discussed in this post, called the Boltzmann machine, is a stochastic and recurrent network. This post contains my exam notes for the course TDT4270 Statistical image analysis and learning and explains...
OpenCL (Open Computing Language) is a new framework for writing programs that execute in parallel on different compute devices (such as CPUs and GPUs) from different vendors (AMD, Intel, ATI, Nvidia etc.). The framework...
Lets say you are working on a website made in Django. And you want to make some nice looking graphs real time, as images from dynamic data. This can be done by using the...
In this essay, written as my final essay in the course IT3708 spring 2010, I discuss two phenomenas that are the driving forces for a lot of the complex biological systems in nature with...
Da var faget Eksperter i Team over og jeg og resten av gruppa mi er stolte over å presentere resultatet av vårt arbeid. Som sagt i et tidligere blogginnlegg gikk oppgaven vår ut på...
I det obligatoriske faget Eksperter i Team har jeg og en gruppe på 3 andre valgt oppgaven med å gjenskape Hamar domkirke i virtuell virkelighet. Det vil si at vi skal modellere den i...
This neural network proposed by Hopfield in 1982 can be seen as a network with associative memory and can be used for different pattern recognition problems. This post contains my exam notes for the...
One often needs a source of random numbers for use in stochastic simulations. Since a computer is deterministic, it can’t generate real random numbers, unless one happen to have a quantum random generator at...
