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
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MonographDOI
Foundations of Data Science
TL;DR: Computer science as an academic discipline began in the 1960’s with emphasis on programming languages, compilers, operating systems, and the mathematical theory that supported these areas, but today, a fundamental change is taking place and the focus is more on applications.
Book ChapterDOI
PUMA: Permission Usage to Detect Malware in Android
Borja Sanz,Igor Santos,Carlos Laorden,Xabier Ugarte-Pedrero,Pablo García Bringas,Gonzalo Alvarez +5 more
TL;DR: PUMA, a new method for detecting malicious Android applications through machine-learning techniques by analysing the extracted permissions from the application itself, is presented.
Journal ArticleDOI
ECG Signal Quality During Arrhythmia and Its Application to False Alarm Reduction
TL;DR: An automated algorithm to assess electrocardiogram (ECG) quality for both normal and abnormal rhythms is presented for false arrhythmia alarm suppression of intensive care unit (ICU) monitors and results suggest that the SQIs should be rhythm specific and that the classifier should be trained for each rhythm call independently.
Journal ArticleDOI
2D Articulated Human Pose Estimation and Retrieval in (Almost) Unconstrained Still Images
TL;DR: This work proposes and proposes and evaluates techniques for searching a video dataset for people in a specific pose, and develops three new pose descriptors and compares their classification and retrieval performance to two baselines built on state-of-the-art object detection models.
Journal ArticleDOI
On physical-layer identification of wireless devices
TL;DR: A systematic review of physical-layer identification systems is presented and a summary of current state-of-the-art techniques is provided to enable a better understanding of device identification, its implications on the analysis and design of security solutions in wireless networks and possible applications.