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Journal ArticleDOI

Pattern Recognition and Machine Learning

Radford M. Neal
- 01 Aug 2007 - 
- Vol. 49, Iss: 3, pp 366-366
TLDR
This book covers a broad range of topics for regular factorial designs and presents all of the material in very mathematical fashion and will surely become an invaluable resource for researchers and graduate students doing research in the design of factorial experiments.
Abstract
(2007). Pattern Recognition and Machine Learning. Technometrics: Vol. 49, No. 3, pp. 366-366.

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Citations
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Tied Factor Analysis for Face Recognition across Large Pose Differences

TL;DR: A generative model that creates a one-to-many mapping from an idealized "identity" space to the observed data space to establish a probabilistic distance metric that allows a full posterior over possible matches to be established.
Book ChapterDOI

Crowd Counting and Profiling: Methodology and Evaluation

TL;DR: This study describes and compares the state-of-the-art methods for video imagery based crowd counting, and provides a systematic evaluation of different methods using the same protocol.
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Objective Automatic Assessment of Rehabilitative Speech Treatment in Parkinson's Disease

TL;DR: This study characterize each of the 156 sustained vowel /a/ phonations with 309 dysphonia measures, select a parsimonious subset using a robust feature selection algorithm, and automatically distinguish the two cohorts (acceptable versus unacceptable) with about 90% overall accuracy.
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Developmental Profiles of Eczema, Wheeze, and Rhinitis: Two Population-Based Birth Cohort Studies

TL;DR: Using data from two population-based birth cohorts, Danielle Belgrave and colleagues examine the evidence for atopic march in developmental profiles for allergic disorders.
Journal ArticleDOI

A review of X-ray explosives detection techniques for checked baggage.

TL;DR: An overview is presented of the various conventional and less conventional approaches that are available to the airline industry, leading to developments in state-of-the-art imaging technology supported by enhanced machine and observer-based decision making principles.