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A Hybrid Deep Learning Pipeline for Wearable Sensors-Based Human Activity Recognition

Year: 2025

Type: article

Abstract: Inertial Sensor-based Daily Activity Recognition (IS-DAR) requires adaptable, data-efficient methods for effective multi-sensor use. This study presents an advanced detection system using body-worn sensors to accurately recog... | Find, read and cite all the research you need on Tech Science Press

Source: Computers, materials & continua/Computers, materials & continua (Print)

DOI: 10.32604/cmc.2025.064601

Authors: Asaad Algarni, Iqra Aijaz Abro, Mohammed Alshehri, Yahya AlQahtani, Abdulmonem Alshahrani, Hui Liu

Institutions: Northern Border University, University of Bremen, King Khalid University, Air University

Language: English

Topic: Context-Aware Activity Recognition Systems

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: Deutsche Forschungsgemeinschaft, King Khalid University, Universität Bremen, Northern Border University

OpenAlex ID: W4412387869