We propose a new fibre tracking algorithm for cardiac DTMRI that parts with the locally "greedy" paradigm intrinsic to conventional tracking algorithms. We formulate the...
In recent years, many principled probabilistic definitions for the determination of visual saliency have been proposed. Moreover, there has been increased focus on the role of con...
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
Early diagnosis and treatment of patients at high risk of developing fragility fractures is crucial in the management of osteoporosis. In this paper we propose to estimate the ris...
We present a browser extension to dynamically learn to filter unwanted images (such as advertisements or flashy graphics) based on minimal user feedback. To do so, we apply the we...