16 citations · 41 across the 7 of their papers we have counts for
5 papers · 1 filter
LiRaNet: End-to-End Trajectory Prediction using Spatio-Temporal Radar Fusion
Meet Shah, Zhiling Huang, Ankit Laddha +5
In this paper, we present LiRaNet, a novel end-to-end trajectory prediction method which utilizes radar sensor information along with widely used lidar and high definition (HD) map…
Conditional Entropy Coding for Efficient Video Compression
Jerry Liu, Shenlong Wang, Wei-Chiu Ma +4
We propose a very simple and efficient video compression framework that only focuses on modeling the conditional entropy between frames. Unlike prior learning-based approaches, we…
A Hypersensitive Breast Cancer Detector
Stefano Pedemonte, Brent Mombourquette, Alexis Goh +6
Early detection of breast cancer through screening mammography yields a 20-35% increase in survival rate; however, there are not enough radiologists to serve the growing population…
Adaptation of a deep learning malignancy model from full-field digital mammography to digital breast tomosynthesis
Sadanand Singh, Thomas Paul Matthews, Meet Shah +6
Mammography-based screening has helped reduce the breast cancer mortality rate, but has also been associated with potential harms due to low specificity, leading to unnecessary exa…
A Multi-site Study of a Breast Density Deep Learning Model for Full-field Digital Mammography Images and Synthetic Mammography Images
Thomas P. Matthews, Sadanand Singh, Brent Mombourquette +12
Purpose: To develop a Breast Imaging Reporting and Data System (BI-RADS) breast density deep learning (DL) model in a multi-site setting for synthetic two-dimensional mammography (…