M
Mayank Kumar
Researcher at Rice University
Publications - 27
Citations - 603
Mayank Kumar is an academic researcher from Rice University. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 4, co-authored 16 publications receiving 484 citations. Previous affiliations of Mayank Kumar include Indian Institutes of Technology.
Papers
More filters
Journal ArticleDOI
DistancePPG: Robust non-contact vital signs monitoring using a camera
TL;DR: DistancePPG as mentioned in this paper proposes a new method of combining skin-color change signals from different tracked regions of the face using a weighted average, where the weights depend on the blood perfusion and incident light intensity in the region, to improve the signal-to-noise ratio (SNR) of camera-based estimate.
Posted Content
DistancePPG: Robust non-contact vital signs monitoring using a camera
TL;DR: DistancePPG as discussed by the authors proposes a new method of combining skin-color change signals from different tracked regions of the face using a weighted average, where the weights depend on the blood perfusion and incident light intensity in the region, to improve the signal-to-noise ratio (SNR) of camera-based estimate.
Journal ArticleDOI
PulseCam: a camera-based, motion-robust and highly sensitive blood perfusion imaging modality.
TL;DR: PulseCam is a new camera-based, motion-robust, and highly sensitive blood perfusion imaging modality with 1 mm spatial resolution and 1 frame-per-second temporal resolution that can detect subtle changes in blood perfusions below the skin with at least two times better sensitivity, three times better response time, and is significantly cheaper compared to infrared thermography.
Proceedings ArticleDOI
PulseCam: High-resolution blood perfusion imaging using a camera and a pulse oximeter
TL;DR: A new multi-sensor modality, named PulseCam, is proposed, for measuring blood perfusion by combining a traditional pulse oximeter with a video camera in a unique way to provide low noise and high-resolution blood perfusions maps.
Proceedings ArticleDOI
Hierarchical Diffusion Models for Singing Voice Neural Vocoder
TL;DR: Experimental results show that the proposed hierarchical diffusion model for singing voice neural vocoders produces high-quality singing voices for multiple singers, outperforming state-of-the-art neural Vocoders with a similar range of computational costs.