Most current methods for multi-class object classification and localization work as independent 1-vs-rest classifiers. They decide whether and where an object is visible in an imag...
When scientific data sets can be interpreted visually they are typically managed as pictures and consequently stored as large collections of bitmaps. Valuable information containe...
We propose a new framework for multi-object segmentation of deep brain structures, which have significant shape variations and relatively small sizes in medical brain images. In th...
The main task in decision tree construction algorithms is to find the "best partition" of the set of objects. In this paper, we investigate the problem of optimal binary ...
—There has been a growing interest in exploiting contextual information in addition to local features to detect and localize multiple object categories in an image. A context mod...