activity
20222024
most citedWeakly Supervised Multi-Task Representation Learning for Human Activity Analysis Using Wearables

28 citations · 56 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2024

Volumetric Mapping with Panoptic Refinement via Kernel Density Estimation for Mobile Robots

Khang Nguyen, Tuan Dang, Manfred Huber

Reconstructing three-dimensional (3D) scenes with semantic understanding is vital in many robotic applications. Robots need to identify which objects, along with their positions an…

eess.SP20242 cited

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…

cs.RO2024

Real-time 3D Semantic Scene Perception for Egocentric Robots with Binocular Vision

K. Nguyen, T. Dang, M. Huber

Perceiving a three-dimensional (3D) scene with multiple objects while moving indoors is essential for vision-based mobile cobots, especially for enhancing their manipulation tasks.…

cs.LG202328 cited

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…

cs.LG20236 cited

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…

cs.HC202320 cited

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…