We present results quantifying the exploitability of compressed remote sensing imagery. The performance of various feature extraction and classification tasks is measured on hype...
Mihaela D. Pal, Christopher M. Brislawn, Steven P....
Abstract. In this paper, we present a graph-based multi-resolution approach for mitosis extraction in breast cancer histological whole slide images. The proposed segmentation uses ...
Vincent Roullier, Olivier Lezoray, Vinh-Thong Ta, ...
Abstract--This paper presents the development of an unsupervised image segmentation framework (referred to as CTex) that is based on the adaptive inclusion of color and texture in ...
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
Recent research on computational modeling of visual attention has demonstrated that a bottom-up approach to identifying salient regions within an image can be applied to diverse a...
Oge Marques, Liam M. Mayron, Gustavo B. Borba, Hum...