We describe an unsupervised method to segment objects detected in images using a novel variant of an interest point template, which is very efficient to train and evaluate. Once a...
Himanshu Arora, Nicolas Loeff, David A. Forsyth, N...
In this paper, we describe an unsupervised segmentation method for contours which proves quite adapted for the images obtained by electronic acquisition. We present two statistica...
This paper presents an unsupervised texture segmentation method, which uses distributions of local binary patterns and pattern contrasts for measuring the similarity of adjacent i...
In recent work, we proposed an alternative to parallel text as translation model (TM) training data: audio recordings of parallel speech (pSp), as it occurs in any communication s...
Abstract. Structural imaging investigations commonly apply a segmentation step followed by the extraction of feature data that can be used to compare or discriminate groups. We pre...