Tag: feature learning

Abstract: In the computer vision literature, many effective histogram-based features have been developed. These engineered features include local binary patterns and edge histogram descriptors among others and they have been shown to be informative features for a variety of computer vision tasks. In this paper, we explore whether these features can be learned through histogram […]

Congratulations to Gatorsense alumni, Changzhe Jiao and Chao Chen,  as well as Alina Zare and collaborators Shuipong Guo, Dong Hai, Bo-Yu Su, Marjorie Skubic , Licheng Jiao and Domonic Ho!  Their paper, “Non-Invasive Heart Rate Estimation from Ballistocardiograms using Bidirectional LSTM Regression,” was recently accepted to the IEEE Journal of Biomedical and Health Informatics (EMB). […]

Abstract: Non-invasive heart rate estimation is of great importance in daily monitoring of cardiovascular diseases. In this paper, a bidirectional long short term memory (bi-LSTM) regression network is developed for non-invasive heart rate estimation from the ballistocardiograms (BCG) signals. The proposed deep regression model provides an effective solution to the existing challenges in BCG heart […]