E-COMMERCE AS A BUSINESS STRATEGY: LESSONS LEARNED FROM CASE STUDIES OF RURAL AND SMALL TOWN BUSINESSES
User-Oriented Machine Learning Strategies for Information Extraction : Putting the Human Back in the Loog
Call for Papers: A Book on Advertising and Reality, UnderContract with: Continuum (Expected Publication Date – Fall 2012)
Machine Vision System for Inspecting Flank Wear on Cutting Tools
A Review of Machine Learning based Anomaly Detection Techniques
Learning Strategies for Story Comprehension : A Reinforcement Learning Approach
Traffic Accident Analysis Using Machine Learning Paradigms
Technologies,Techniques for Collaboration, Information Sharing
Practical Machine Learning
Case Studies in M2M by David Wigglesworth of Iridium
Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Applying machine learning techniques to multimedia content involves special considerations – the data is typically of very high dimension, and the normal distinction between supervised and unsupervised techniques does not always apply.
This book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain. Arising from the EU MUSCLE network, a program that drew together multidisciplinary teams with expertise in machine learning, pattern recognition, artificial intelligence, and image, video, text and crossmedia processing, the book first introduces the machine learning principles and techniques that are applied in multimedia data processing and analysis. The second part focuses on multimedia data processing applications, with chapters examining specific machine learning issues in domains such as image retrieval, biometrics, semantic labelling, mobile devices, and mining in text and music.
This book will be suitable for practitioners, researchers and students engaged with machine learning in multimedia applications.
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