A Survey of Crowdsourcing in Medical Image Analysis

Rapid advances in image processing capabilities have been seen across many domains, fostered by the application of machine learning algorithms to "big-data". However, within the realm of medical image analysis, advances have been curtailed, in part, due to the limited availability of large-scale, well-annotated datasets. One of the main reasons...

Dissimilarity-Based Multiple Instance Learning

Multiple instance learning (MIL) is an extension of supervised learning where the objects are represented by sets (bags) of feature vectors (instances) rather than individual feature vectors. For example, an image can be represented by a bag of instances, where each instance is a patch in that image. Only bag labels are given, however, the...

On the Informativeness of Asymmetric Dissimilarities (abstract)

Nearest-neighbor (NN) classification has been widely used in many research areas, as it is a very intuitive technique. As long as we can defined a similarity or distance between two objects, we can apply NN, therefore making it suitable even for non-vectorial data such as graphs. An alternative to NN is the dissimilarity space [2], where...

Using Pattern Recognition Techniques for Server Overload Detection

One of the key factors in customer satisfaction is application performance. To be able to guarantee good performance, it is necessary to take appropriate measures before a server overload occurs. While in small systems it is usually possible to predict server overload using a subjective human expert, an automated overload prediction mechanism is...

Random Subspace Method for One-Class Classifiers

Project Phantom

Report for the course IN3700 (Bachelor project). In this case the project was to make a game called Project Phantom. The project was in collaboration with CannibalGameStudios which supplied the project and the tutoring.