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In this paper, to cope with these two challenges, we use transfer learning to build personalized models and model compression for running DL algorithms.
Jul 1, 2023 · We use transfer learning (TL) to build personalized models for Human Activity Recognition (HAR). •. We compress DL models using quantization to ...
Another challenge is running deep learning (DL) models on mobile and wearable devices due to their limited resources. In this paper, to cope with these two ...
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Personalized and motion-based human activity recognition with transfer learning and compressed deep learning models. Computers and Electrical Engineering ...
This survey aims to provide an overview of the state-of-the-art in HAR, focusing on new techniques such as multimodality, Deep Reinforcement Learning (DRL) and ...
This work presents an on-device machine learning model with the ability to identify different mobility gestures called human activity recognition (HAR).
Jun 27, 2023 · Abstract- The use of video surveillance for human activity recognition (HAR) in inpatient rehabilitation, activity recognition, or mobile ...
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Personalized and motion-based human activity recognition with transfer learning and compressed deep learning models. Article. Jul 2023; COMPUT ELECTR ENG.
Jan 28, 2021 · Personalized Human Activity Recognition Based on Integrated Wearable Sensor and Transfer Learning.
Nine different HAR models are trained by traditional machine learning and transfer learning methods. The experimental results show that the multi-modal data ...