Journal ArticleDOI
Pattern Recognition and Machine Learning
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.read more
Citations
More filters
Journal ArticleDOI
An Online One Class Support Vector Machine-Based Person-Specific Fall Detection System for Monitoring an Elderly Individual in a Room Environment
TL;DR: From the comprehensive experimental evaluations on datasets for 12 people, it is confirmed that the proposed person-specific fall detection system can achieve excellent fall detection performance with 100% fall detection rate and only 3% false detection rate with the optimally tuned parameters.
Journal ArticleDOI
On optimality of kernels for approximate Bayesian computation using sequential Monte Carlo
TL;DR: This paper discusses how to construct the perturbation kernels that are required in ABC SMC approaches, in order to construct a sequence of distributions that start out from a suitably defined prior and converge towards the unknown posterior.
Proceedings ArticleDOI
Stochastic collapsed variational Bayesian inference for latent Dirichlet allocation
TL;DR: This article proposed a stochastic algorithm for collapsed variational Bayesian inference for LDA, which is simpler and more efficient than the state-of-the-art method, and showed that the algorithm converges faster and often to a better solution than previous methods.
Journal ArticleDOI
Early drought stress detection in cereals: simplex volume maximisation for hyperspectral image analysis
Christoph Römer,Mirwaes Wahabzada,Agim Ballvora,Francisco de Assis de Carvalho Pinto,Micol Rossini,Cinzia Panigada,Jan Behmann,Jens Léon,Christian Thurau,Christian Bauckhage,Kristian Kersting,Uwe Rascher,Lutz Plümer +12 more
TL;DR: This work applies for the first time a recent matrix factorisation technique, simplex volume maximisation (SiVM), to hyperspectral data, an unsupervised classification approach, optimised for fast computation of massive datasets.
Journal ArticleDOI
Prostate Cancer Detection using Deep Convolutional Neural Networks.
TL;DR: In this paper, the authors developed and implemented an automated CNN-based pipeline for detection of clinically significant prostate cancer (PCa) for a given axial DWI image and for each patient.