|Neural network||Link to webpage||Neural Network Simulation: The recognition application||Maurice Peemen|
|Biomedical imaging||Link to webpage||Optimizing a Biomedical Imaging Orientation Score Framework||Cedric Nugteren|
|Neural network training||Link to webpage||Efficient mapping of the training of Convolutional Neural Networks to a CUDA-based cluster||Maurice Peemen|
|Scene reconstruction||Link to webpage||Optimization of a 3D Scene Reconstruction Application||Zhenyu Ye|
|Satellite image projection||Link to webpage||Optimizing the Proba-V mapping algorithm implementation for a heterogenous (CPU + GPU) environment||Gert-Jan van den Braak|
In 2012 two groups of five students have worked on mapping the SIFT object recognition application to the GPU cluster. With the SIFT algorithm objects can be found in images or videos independent of their scale, orientation or illumiation. Even partially covered objects can be found.
The goal of this project is to find a coffee mug between a pile of clutter on a desk in some office. An image of the coffee mug (the object) is shown on the right. The video of the desk in the office is shown below, next to the output video with the coffee mug highlighted.
The results of the two groups can be found on their webpages: