Traditional binary hypothesis testing relies on the precise knowledge of the probability density of an observed random vector conditioned on each hypothesis. However, for many app...
Segmentation of deep brain structures is a challenging task for MRI images due to blurry structure boundaries, small object size and irregular shapes. In this paper, we present a ...
Recognizing the location and orientation of a mobile device from captured images is a promising application of image retrieval algorithms. Matching the query images to an existing...
Georg Schroth, Anas Al-Nuaimi, Robert Huitl, Flori...
The goal of emotion classification is to estimate an emotion label, given representative data and discriminative features. Humans are very good at deriving high-level representat...
We describe the Arabic broadcast transcription system elded by IBM in the GALE Phase 4 machine translation evaluation. Key advances over our Phase 3.5 system include improvements ...
Brian Kingsbury, Hagen Soltau, George Saon, Stephe...
In video coding systems using adaptive arithmetic coding to compress texture information, the employed symbol probability models need to be retrained every time the coding process...
Kenneth Vermeirsch, Joeri Barbarien, Peter Lambert...
In this paper, we propose a method to extract features from three-dimensional acceleration signals. The proposed method is based on the (auto-)correlation matrix of Fourier transf...
We propose a kernelized maximal-figure-of-merit (MFoM) learning approach to efficiently training a nonlinear model using subspace distance minimization. In particular, a fixed,...
Cashiers in retail stores usually exhibit certain repetitive and periodic activities when processing items. Detecting such activities plays a key role in most retail fraud detecti...
This paper presents a new method to automatically add n-grams containing out-of-vocabulary (OOV) words to a baseline language model (LM), where these n-grams are sought to be gram...