35 citations · 127 across the 42 of their papers we have counts for
3 papers · 1 filter
PIM: Physics-Informed Multi-task Pre-training for Improving Inertial Sensor-Based Human Activity Recognition
Dominique Nshimyimana, Vitor Fortes Rey, Sungho Suh +2
Human activity recognition (HAR) with deep learning models relies on large amounts of labeled data, often challenging to obtain due to associated cost, time, and labor. Self-superv…
Assessing the Impact of Sampling Irregularity in Time Series Data: Human Activity Recognition As A Case Study
Mengxi Liu, Daniel Geißler, Sizhen Bian +2
Human activity recognition (HAR) ideally relies on data from wearable or environment-instrumented sensors sampled at regular intervals, enabling standard neural network models opti…
Initial Findings on Sensor based Open Vocabulary Activity Recognition via Text Embedding Inversion
Lala Shakti Swarup Ray, Bo Zhou, Sungho Suh +1
Conventional human activity recognition (HAR) relies on classifiers trained to predict discrete activity classes, inherently limiting recognition to activities explicitly present i…