In this paper, we propose a general framework for fusing bottom-up segmentation with top-down object behavior classification over an image sequence. This approach is beneficial fo...
Abstract. We propose a semi-supervised, kinetic modeling based segmentation technique for molecular imaging applications. It is an iterative, self-learning algorithm based on uncer...
Ahmed Saad, Benjamin Smith 0002, Ghassan Hamarneh,...
Models of spatial variation in images are central to a large number of low-level computer vision problems including segmentation, registration, and 3D structure detection. Often, i...
—This work aims at investigating the influence of luminance information and environment illumination on skin classification. We explore Bayesian approaches to perform automatic...
Diogo Kuiaski, Hugo Vieira Neto, Gustavo B. Borba,...
In this paper we present a learning based method for vessel segmentation in angiographic videos. Vessel Segmentation is an important task in medical imaging and has been investiga...