Activity Recognition: Fundamentals and Applications

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What Is Activity Recognition

Activity recognition is an approach that makes use of a number of observations on the activities of one or more agents, as well as the conditions of their surrounding environment, with the end goal of identifying the actions and objectives of those individuals. Because of its ability to offer personalized support for a wide variety of applications and its connections to a wide variety of other fields of study, such as medicine, human-computer interaction, or sociology, this area of research has attracted the attention of several communities within the field of computer science since the 1980s.


How You Will Benefit


(I) Insights, and validations about the following topics:


Chapter 1: Activity recognition


Chapter 2: Computer vision


Chapter 3: Artificial neural network


Chapter 4: Machine learning


Chapter 5: Gesture recognition


Chapter 6: Recurrent neural network


Chapter 7: Context awareness


Chapter 8: Transfer learning


Chapter 9: Convolutional neural network


Chapter 10: List of datasets for machine-learning research


(II) Answering the public top questions about activity recognition.


(III) Real world examples for the usage of activity recognition in many fields.


(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of activity recognition' technologies.


Who This Book Is For


Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of activity recognition.

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