SETransformer combines a Transformer encoder, channel attention, and attention pooling for WISDM activity recognition, but the architecture is permutation-invariant and the reported comparison omits the model itself.
A survey on deep learning architectures in human activities recog- nition application in sports science, healthcare, and secu- rity
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SETransformer: A Hybrid Attention-Based Architecture for Robust Human Activity Recognition
SETransformer combines a Transformer encoder, channel attention, and attention pooling for WISDM activity recognition, but the architecture is permutation-invariant and the reported comparison omits the model itself.