28 citations · 60 across the 5 of their papers we have counts for
5 papers
Reducing Label Dependency in Human Activity Recognition with Wearables: From Supervised Learning to Novel Weakly Self-Supervised Approaches
Taoran Sheng, Manfred Huber
Human activity recognition (HAR) using wearable sensors has advanced through various machine learning paradigms, each with inherent trade-offs between performance and labeling requ…
Consistency Based Weakly Self-Supervised Learning for Human Activity Recognition with Wearables
Taoran Sheng, Manfred Huber
While the widely available embedded sensors in smartphones and other wearable devices make it easier to obtain data of human activities, recognizing different types of human activi…
Weakly Supervised Multi-Task Representation Learning for Human Activity Analysis Using Wearables
Taoran Sheng, Manfred Huber
Sensor data streams from wearable devices and smart environments are widely studied in areas like human activity recognition (HAR), person identification, or health monitoring. How…
Unsupervised Embedding Learning for Human Activity Recognition Using Wearable Sensor Data
Taoran Sheng, Manfred Huber
The embedded sensors in widely used smartphones and other wearable devices make the data of human activities more accessible. However, recognizing different human activities from t…
Siamese Networks for Weakly Supervised Human Activity Recognition
Taoran Sheng, Manfred Huber
Deep learning has been successfully applied to human activity recognition. However, training deep neural networks requires explicitly labeled data which is difficult to acquire. In…