The transition from structures to textures in magnetorheological fluids

A magnetorheological fluid is a type of smart fluid that can change its rheological properties when a magnetic field is applied to the fluid. The fluid is a suspension of magnetizable particles in a non-magnetic carrier fluid. When a magnetic field is applied to the fluid, the particles will form structures along the magnetic field lines. These...

Design and Implementation of Real-Time High-Defnition Stereo Matching SoC on FPGA

Stereo matching has been widely used in many fields, such as viewpoint interpolation, feature detection system and free-view TV. However, the long processing time of stereo matching algorithms has been the major bottleneck that limits their real-time applications. During the past decades, many implementation platforms and corresponding algorithm...

Acceleration of the Multi Level Fast Multipole Algorithm on a Graphics Processing Unit

It is of great importance that enemy aircraft can be detected by a radar. Good knowledge about one’s own detectability is also needed to make one’s own visibility as low as possible. Obtaining the aircraft radar signature involves solving a scattering problem with a large, low-observable aircraft. Briefly explained; the incident radar wave...

Feasibilty Analysis for Hardware Acceleration of Pattern Recognition Algorithms

This thesis presents a feasibility analysis for hardware acceleration of the pattern recognition algorithms used by the Media Knowledge Engineering department at the Delft University of Technology. The feasibility analysis is conducted on a number of different algorithm classes. The Parzen Window algorithm appeared to be the most suitable option...

Optimization of Texture Feature Extraction Algorithm

Texture, the pattern of information or arrangement of the structure found in an image, is an important feature of many image types.In a general sense, texture refers to surface characteristics and appearance of an object given by the size, shape, density, arrangement, proportion of its elementary parts. Due to the signification of texture...

High-Speed Object Detection: Design, Study and Implementation of a Detection Framework using Channel Features and Boosting

In this thesis we design, implement and study a high-speed object detection framework. Our baseline detector uses integral channel features as object representation and AdaBoost as supervised learning algorithm. We suggest the implementation of two approximation techniques for speeding up the baseline detector and show their effectiveness by...

Evaluating Novel Matrix-Vector Multiplication Strategies in the LSTRS and TRUSTµ Methods for Large-Scale Trust-Region Subproblems and Regularization

In the regularization of ill-posed problems from image restoration, where we want to recover an image from blurred and noisy data, there are many methods that can be useful. Among those, the TRUSTmu method proposed in Rojas and Steihaug, 2002, is an efficient method for solving large-scale regularization problems with additional non-negativity...

Adaptive Reinforcement Learning: Increasing the applicability for large and time varying systems using parallel Gaussian Process regression and adaptive nonlinear control

This thesis investigates the applicability of the Probabilistic Inference for Learning COntrol (PILCO) algorithm to large systems and systems with time varying measurement noise. PILCO is a state-of-the-art model-learning Reinforcement Learning (RL) algorithm that uses a Gaussian Process (GP) model to average over uncertainties during learning....

Distributed ParaPy - Increasing The Computational Efficiency of KBE Models

As Knowledge Based Engineering (KBE) is gaining in popularity in the industry, the models developed with the technology grow in complexity. The larger KBE models suffer from long (re)generation times and outgrow the memory resources of standard desktop computer. In the meantime, the number of cores present in computer’s processors is steadily...