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This paper considers the problem of estimating the focus of expansion of optical flow fields from panoramic image sequences due to ego-motion of the camera. The focus of expansion provides a measurement of the direction of motion of the vehicle that is a k ...
We present a diffusion-based bias-compensated recursive least squares (RLS) algorithm for distributed estimation in ad-hoc adaptive sensor networks where nodes cooperate to estimate a common deterministic parameter vector. It is assumed that both the regre ...
Flood quantile estimation is of great importance for several types of engineering studies and policy decisions. However, practitioners must often deal with the limited availability of data and with short-length observation series. Thus, the information mus ...
We introduce a classification-based approach to finding occluding texture boundaries. The classifier is composed of a set of weak lear ners which operate on image intensity discriminative features which are defined on small patches and fast to compute. A d ...
Institute of Electrical and Electronics Engineers2009
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 ...
Time series modeling and analysis is central to most financial and econometric data modeling. With increased globalization in trade, commerce and finance, national variables like gross domestic productivity (GDP) and unemployment rate, market variables lik ...
The rapid accumulation of whole-genome data has renewed interest in the study of genomic rearrangements. Comparative genomics, evolutionary biology, and cancer research all require models and algorithms to elucidate the mechanisms, history, and consequence ...
The rapid accumulation of whole-genome data has renewed interest in the study of genomic rearrangements. Comparative genomics, evolutionary biology, and cancer research all require models and algorithms to elucidate the mechanisms, history, and consequence ...
In this paper, we consider model combination methods for adaptive filtering that perform unbiased estimation. In this widely studied framework, two adaptive filters are run in parallel, each producing unbiased estimates of an underlying linear model. The o ...
This paper presents a new paradigm for choice set generation in the context of route choice model estimation. We assume that the choice sets contain all paths connecting each origin-destination pair. Although this is behaviorally questionable, we make this ...
