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Context-Aware Complex Human Activity Recognition Using Hybrid Deep Learning Models
2022
Applied Sciences
Smart devices, such as smartphones, smartwatches, etc., are examples of promising platforms for automatic recognition of human activities. However, it is difficult to accurately monitor complex human activities on these platforms due to interclass pattern similarities, which occur when different human activities exhibit similar signal patterns or characteristics. Current smartphone-based recognition systems depend on traditional sensors, such as accelerometers and gyroscopes, which are built-in
doi:10.3390/app12189305
fatcat:vsacnsocjne2bmq4kwfj2wqe2m