17 citations · 40 across the 31 of their papers we have counts for
9 papers · 1 filter
ChairPose: Pressure-based Chair Morphology Grounded Sitting Pose Estimation through Simulation-Assisted Training
Lala Shakti Swarup Ray, Vitor Fortes Rey, Bo Zhou +2
Prolonged seated activity is increasingly common in modern environments, raising concerns around musculoskeletal health, ergonomics, and the design of responsive interactive system…
On the Generalization Limits of Quantum Generative Adversarial Networks with Pure State Generators
Jasmin Frkatovic, Akash Malemath, Ivan Kankeu +7
We investigate the capabilities of Quantum Generative Adversarial Networks (QGANs) in image generations tasks. Our analysis centers on fully quantum implementations of both the gen…
TinierHAR: Towards Ultra-Lightweight Deep Learning Models for Efficient Human Activity Recognition on Edge Devices
Sizhen Bian, Mengxi Liu, Vitor Fortes Rey +2
Human Activity Recognition (HAR) on resource-constrained wearable devices demands inference models that harmonize accuracy with computational efficiency. This paper introduces Tini…
Combining Human-centred Explainability and Explainable AI
Janin Koch, Vitor Fortes Rey
This position paper looks at differences between the current understandings of human-centered explainability and explainability AI. We discuss current ideas in both fields, as well…
Boosting Classification with Quantum-Inspired Augmentations
Matthias Tschöpe, Vitor Fortes Rey, Sogo Pierre Sanon +3
Understanding the impact of small quantum gate perturbations, which are common in quantum digital devices but absent in classical computers, is crucial for identifying potential ad…
TxP: Reciprocal Generation of Ground Pressure Dynamics and Activity Descriptions for Improving Human Activity Recognition
Lala Shakti Swarup Ray, Lars Krupp, Vitor Fortes Rey +3
Sensor-based human activity recognition (HAR) has predominantly focused on Inertial Measurement Units and vision data, often overlooking the capabilities unique to pressure sensors…
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…
Hybrid CNN-Dilated Self-attention Model Using Inertial and Body-Area Electrostatic Sensing for Gym Workout Recognition, Counting, and User Authentification
Sizhen Bian, Vitor Fortes Rey, Siyu Yuan +1
While human body capacitance () has been explored as a novel wearable motion sensing modality, its competence has never been quantitatively demonstrated compared to that of th…
Collaborative Human Activity Recognition with Passive Inter-Body Electrostatic Field
Sizhen Bian, Vitor Fortes Rey, Siyu Yuan +1
The passive body-area electrostatic field has recently been aspiringly explored for wearable motion sensing, harnessing its two thrilling characteristics: full-body motion sensitiv…