A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
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This article is published in Annals of Mathematical Statistics.The article was published on 1970-02-01 and is currently open access. It has received 4618 citations till now. The article focuses on the topics: Examples of Markov chains & Markov chain.read more
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Development of head detection and tracking systems for visual surveillance
TL;DR: The novelty of this paper is derived from differences in real-time input images, preprocessing to remove noises (morphological operators and so on), detecting edge lines and restoration, finding the face area, and cutting the head candidate.
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A Spectral Algorithm for Learning Hidden Markov Models
TL;DR: It is proved that under a natural separation condition (bounds on the smallest singular value of the HMM parameters), there is an efficient and provably correct algorithm for learning HMMs.
Local models and Gaussian mixture models for statistical data processing
TL;DR: Local models or Gaussian mixture models can be efficient tools for dimension reduction, exploratory data analysis, feature extraction, classification and regression, and proposed algorithms for regularizing them are presented.
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Independent shape component-based human activity recognition via Hidden Markov Model
TL;DR: A novel human activity recognition method is proposed, which utilizes Independent Component Analysis for activity shape information extraction from image sequences and Hidden Markov Model (HMM) for recognition.
Proceedings ArticleDOI
Behavior recognition based on machine learning algorithms for a wireless canine machine interface
TL;DR: A canine body-area-network (cBAN) is developing to combine sensing technologies and computational modeling to provide handlers with a more accurate interpretation for dog training to facilitate less subjective and lower-cost training techniques.
References
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Journal ArticleDOI
Statistical Inference for Probabilistic Functions of Finite State Markov Chains
Leonard E. Baum,Ted Petrie +1 more
Journal ArticleDOI
An inequality with applications to statistical estimation for probabilistic functions of Markov processes and to a model for ecology
Leonard E. Baum,J. A. Eagon +1 more
TL;DR: In this paper, a polynomial with nonnegative coefficients homogeneous of degree d in its variables is shown to be polynomially homogeneous unless 3(3(x))>P(x), where 3(x)=x.
Book ChapterDOI
The Gamma Function
Willi Freeden,Martin Gutting +1 more
TL;DR: The Gamma function as discussed by the authors is a generalized factorial function that can be used to estimate the probability distribution of a probability distribution, and it has been used in many applications, e.g., as part of probability distributions.