A multilayer interval type-2 fuzzy extreme learning machine for the recognition of walking activities and gait events using wearable sensors
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Autoencoders are most commonly used for feature extraction and dimensionality reduction.
“As such, autoencoders are most commonly used for feature extraction and dimensionality reduction [120,122,123,124,125,126,133,134,135,136,137,138,139,140,141].”
From Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances (2022) · cites this paper as [123]
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Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances
Zhang, S., Li, Y., Zhang, S., Shahabi, F., Xia, S., Deng, Y., & Alshurafa, N. (2022) · Sensors · doi:10.3390/s22041476 · Cited by 625 · see citing works
“As such, the outputs of autoencoders are often used as inputs to other networks and algorithms to improve performance [120, 121, 122, 123, 124].”
BackgroundMethodMachine Learning and AI Technologies for Smart Wearables
Seng, K. P., Ang, L.-M., Peter, E., & Mmonyi, A. (2023) · Electronics · doi:10.3390/electronics12071509 · Cited by 90 · see citing works
- Authors
- Rubio-Solis, A., Panoutsos, G., Beltran-Perez, C., & Martinez-Hernandez, U.
- Affiliations
- University of Sheffield (GB)
- Corresponding author
- Rubio-Solis, Adrian
- Venue
- Neurocomputing
- Publisher
- Elsevier BV
- Published
- 2020-05
- Volume
- 389
- Pages
- 42-55
- ISSN
- 0925-2312 (ISSN-L)
- OpenAlex
- W2994286812
- Cited by
- 39
- References
- 54
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 6 · 2023: 8 · 2022: 6 · 2021: 7 · 2020: 7
- FWCI
- 2.75
- Type
- journal article
- Language
- en
- Open access
- Locations
- Neurocomputing (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- Pure (University of Bath) (submittedVersion, cc-by)
- Greater South Information System
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Fuzzy Logic and Control Systems
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and ELM
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- interval type-2 fuzzy logic, extreme learning machine, wearable inertial sensors, hierarchical learning, stance and swing phases, sensor noise robustness
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