Easy Ensemble: Simple Deep Ensemble Learning for Sensor-Based Human Activity Recognition

Author:

Hasegawa Tatsuhito1ORCID,Kondo Kazuma1

Affiliation:

1. Fundamental Engineering for Knowledge-Based Society, Graduate School of Engineering, University of Fukui, Fukui, Japan

Funder

Japan Society for the Promotion of Science (JSPS) KAKENHI Grant-in-Aid for Early-Career Scientists

Research Grants from the University of Fukui

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Reference53 articles.

1. Aggregated Residual Transformations for Deep Neural Networks

2. MotherNets: Rapid deep ensemble learning;wasay;Proc Int Conf Mach Learn Syst,2020

3. Sensor Based Human Activity Recognition Using Adaboost Ensemble Classifier

4. Group ensemble: Learning an ensemble of ConvNets in a single ConvNet;chen;arXiv 2007 00649,2020

5. Multi-input CNN-GRU based human activity recognition using wearable sensors

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1. Chinese relation extraction in military field based on multi-grained lattice transformer and imbalanced data classification;International Journal of Modeling, Simulation, and Scientific Computing;2023-11-15

2. Implementation of a Human Activity Monitoring System through IoT Sensor and Blynk Cloud Platform;Journal of Information Technology and Digital World;2022-07-19

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