IoT-Based Multisensors Fusion for Activity Recognition via Key Features and Hybrid Transfer Learning

IoT-Based Multisensors Fusion for Activity Recognition via Key Features and Hybrid Transfer Learning

Human activity recognition (HAR) has attracted significant attention in various fields, including healthcare, smart homes, and human-computer interaction. Accurate HAR can enhance user experience, provide critical health insights, and enable sophisticated context-aware applications. This paper prese...

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Bibliographic Details
Main Authors: Ahmad Jalal, Danyal Khan, Touseef Sadiq, Moneerah Alotaibi, Sultan Refa Alotaibi, Hanan Aljuaid, Hameedur Rahman
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Human activity recognition (HAR)
RGB videos
IMU sensor data
Naive Bayes segmentation
recurrent neural network (RNN)
Shapley additive explanations (SHAP)
Online Access:https://ieeexplore.ieee.org/document/10818665/
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https://ieeexplore.ieee.org/document/10818665/

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