Activity Learning

Discovering, Recognizing, and Predicting Human Behavior from Sensor Data de

,

Éditeur :

Wiley


Collection :

Wiley Series on Parallel and Distributed Computing

Paru le : 2015-02-19

eBook Téléchargement , DRM LCP 🛈 DRM Adobe 🛈
Lecture en ligne (streaming)
117,05

Téléchargement immédiat
Dès validation de votre commande
Image Louise Reader présentation

Louise Reader

Lisez ce titre sur l'application Louise Reader.

Description

Defines the notion of an activity model learned from sensor data and presents key algorithms that form the core of the field
Activity Learning: Discovering, Recognizing and Predicting Human Behavior from Sensor Data provides an in-depth look at computational approaches to activity learning from sensor data. Each chapter is constructed to provide practical, step-by-step information on how to analyze and process sensor data. The book discusses techniques for activity learning that include the following: Discovering activity patterns that emerge from behavior-based sensor data Recognizing occurrences of predefined or discovered activities in real time Predicting the occurrences of activities
The techniques covered can be applied to numerous fields, including security, telecommunications, healthcare, smart grids, and home automation. An online companion site enables readers to experiment with the techniques described in the book, and to adapt or enhance the techniques for their own use.

With an emphasis on computational approaches, Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data provides graduate students and researchers with an algorithmic perspective to activity learning.
Pages
288 pages
Collection
Wiley Series on Parallel and Distributed Computing
Parution
2015-02-19
Marque
Wiley
EAN papier
9781118893760
EAN PDF
9781119010234

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
288
Taille du fichier
10045 Ko
Prix
117,05 €
EAN EPUB
9781119010241

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
288
Taille du fichier
15565 Ko
Prix
117,05 €