Joint Learning of Temporal Models to Handle Imbalanced Data for Human Activity Recognition
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Title
Joint Learning of Temporal Models to Handle Imbalanced Data for Human Activity Recognition
Authors
Keywords
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Journal
Applied Sciences-Basel
Volume 10, Issue 15, Pages 5293
Publisher
MDPI AG
Online
2020-07-31
DOI
10.3390/app10155293
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- An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox
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- Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors
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- A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches
- (2011) M. Galar et al. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND RE
- An activity monitoring system for elderly care using generative and discriminative models
- (2010) T. L. M. van Kasteren et al. Personal and Ubiquitous Computing
- Learning from Imbalanced Data
- (2009) Haibo He et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
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