Enhancing FT-Transformer With a Matérn-Driven Kolmogorov-Arnold Feature Tokenizer for Tabular Data-Based In-Bed Posture Classification
In-bed posture classification plays a crucial role in health monitoring. In this paper, we explore in-bed posture classification using FT-Transformer, a model that employs 1D tabular inputs instead of the commonly used 2D pressure heatmaps. However, the Feature Tokenizer in FT-Transformer suffers fr...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11075767/ |
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