Automatic floor segmentation can serve many interesting purposes including mixed reality (MR) applications, interior design, entertainment, computation of available space in a room, or indoor robot navigation. In this project, we have been solving a problem of scene understanding and, in particular, determining which pixels of the image belong to the floor. The problem of floor segmentation is a good example of how the same task can be solved with classical computer vision algorithms or deep learning.
The task of accurate cell segmentation is essential for cellular biology and single-cell analysis, as well as for studying biological processes as a whole. In biomedical image processing, this includes reconstruction of microscopy images, foreground segmentation, cell detection, cellular compartments and organelles segmentation. Despite the tremendous progress in microscopy cell imaging and numerous segmentation methods, accurate segmentation and reliable characterization of cells remain challenging tasks that usually require problem-specific tailoring of algorithms.