Cargando…
Robust Human Activity Recognition by Integrating Image and Accelerometer Sensor Data Using Deep Fusion Network
Studies on deep-learning-based behavioral pattern recognition have recently received considerable attention. However, if there are insufficient data and the activity to be identified is changed, a robust deep learning model cannot be created. This work contributes a generalized deep learning model t...
Autores principales: | Kang, Junhyuk, Shin, Jieun, Shin, Jaewon, Lee, Daeho, Choi, Ahyoung |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8747696/ https://www.ncbi.nlm.nih.gov/pubmed/35009717 http://dx.doi.org/10.3390/s22010174 |
Ejemplares similares
-
Human Postures Recognition by Accelerometer Sensor and ML Architecture Integrated in Embedded Platforms: Benchmarking and Performance Evaluation
por: Leone, Alessandro, et al.
Publicado: (2023) -
Accelerometer-Based Human Activity Recognition for Patient Monitoring Using a Deep Neural Network
por: Fridriksdottir, Esther, et al.
Publicado: (2020) -
A Robust End-to-End Deep Learning-Based Approach for Effective and Reliable BTD Using MR Images
por: Ullah, Naeem, et al.
Publicado: (2022) -
Sensor Data Acquisition and Multimodal Sensor Fusion for Human Activity Recognition Using Deep Learning
por: Chung, Seungeun, et al.
Publicado: (2019) -
Robust Korean License Plate Recognition Based on Deep Neural Networks
por: Wang, Hanxiang, et al.
Publicado: (2021)