An Adaptive Approach for Online Segmentation of Multi-Dimensional Mobile Data
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Prior research into the link between new product development and market segmentation has focused on two main approaches: (1) design, segment, and do limited competitive evaluation; and (2) segment first, design second. This paper proposes a third approach, ...
The objective of this diploma thesis was the recognition of vehicles, with perspective to generate a knowledge base for the automatic recognition of vehicles from similar type of data. The goal was achieved by developing a knowledge base in the object-orie ...
In this paper, we investigate the effect of temporal context for speech/non-speech detection (SND). It is shown that even a simple feature such as full-band energy, when employed with a large-enough context, shows promise for further investigation. Experim ...
Segmentation of moving objects in image sequences plays an important role in video processing and analysis. Evaluating the quality of segmentation results is necessary to allow the appropriate selection of segmentation algorithms and to tune their paramete ...
An important problem in logistic regression modeling is the existence of the maximum likelihood estimators. In particular, when the sample size is small, the maximum likelihood estimator of the regression parameters does not exist if the data are completel ...
Mixed logit models can represent heterogeneity across individuals, in both observed and unobserved preferences, but require computationally expensive calculations to compute probabilities. A few methods for including error covariance heterogeneity in a clo ...
Mixed logit models can represent heterogeneity across individuals, in both observed and unobserved preferences, but require computationally expensive calculations to compute probabilities. A few methods for including error covariance heterogeneity in a clo ...
We introduce a new approach for finger-spelling recognition from video sequences, relying on the collaboration between the feature extraction and behavior inference processes. The inference process dynamically guides the segmentation- based feature extract ...
Generalized Linear Models have become a commonly used tool of data analysis. Such models are used to fit regressions for univariate responses with normal, gamma, binomial or Poisson distribution. Maximum likelihood is generally applied as fitting method. I ...
This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, ...