June 2019
Intermediate to advanced
308 pages
7h 21m
English
Content preview from Hands-On Deep Learning for IoT
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Automatic human activity recognition system
Automatic human activity recognition (HAR) systems detect human activity, based on raw accelerometer and gyroscope signals. The following diagram shows a schematic of a DL-based HAR that consists of three different phases. They are as follows:
- IoT deployment or instrumentation of the subject or person
- Feature extraction and model development
- Activity classification/identification
Generally, classical HAR approaches mainly rely on heuristic hand-crafted feature extraction methods, which is a complex process and not well suited for resource-constrained IoT devices. More recent DL-based HAR approaches ...
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