BenchHAR finds that hybrid reconstruction-plus-contrastive SSL with CNN encoders generalizes best for sensor HAR but overall performance on unseen distributions remains unsatisfactory.
WISDM Smartphone and Smartwatch Activity and Biometrics Dataset
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
Dual-stream statistical plus deep-embedding pipeline with rehearsal yields competitive accuracy and low forgetting on five time-series benchmarks for class-incremental classification.
citing papers explorer
-
BenchHAR: Benchmarking Self-Supervised Learning for Generalizable Sensor-based Activity Recognition
BenchHAR finds that hybrid reconstruction-plus-contrastive SSL with CNN encoders generalizes best for sensor HAR but overall performance on unseen distributions remains unsatisfactory.
-
Combining Statistical Features and Deep Encodings for Rehearsal-Based Class-Incremental Time Series Classification
Dual-stream statistical plus deep-embedding pipeline with rehearsal yields competitive accuracy and low forgetting on five time-series benchmarks for class-incremental classification.