84 citations · 88 across the 5 of their papers we have counts for
6 papers
Learning Unified Representations of Normalcy for Time Series Anomaly Detection
Prithul Sarker, Sushmita Sarker, Nicholas G. Murray +1
The core challenge in unsupervised anomaly detection is identifying abnormal patterns without prior knowledge of their characteristics. While existing methods have addressed aspect…
Guided and Unguided Conditional Diffusion Mechanisms for Structured and Semantically-Aware 3D Point Cloud Generation
Gunner Stone, Sushmita Sarker, Alireza Tavakkoli
Generating realistic 3D point clouds is a fundamental problem in computer vision with applications in remote sensing, robotics, and digital object modeling. Existing generative app…
Can Score-Based Generative Modeling Effectively Handle Medical Image Classification?
Sushmita Sarker, Prithul Sarker, George Bebis +1
The remarkable success of deep learning in recent years has prompted applications in medical image classification and diagnosis tasks. While classification models have demonstrated…
A comprehensive overview of deep learning techniques for 3D point cloud classification and semantic segmentation
Sushmita Sarker, Prithul Sarker, Gunner Stone +4
Point cloud analysis has a wide range of applications in many areas such as computer vision, robotic manipulation, and autonomous driving. While deep learning has achieved remarkab…
MV-Swin-T: Mammogram Classification with Multi-view Swin Transformer
Sushmita Sarker, Prithul Sarker, George Bebis +1
Traditional deep learning approaches for breast cancer classification has predominantly concentrated on single-view analysis. In clinical practice, however, radiologists concurrent…
ConnectedUNets++: Mass Segmentation from Whole Mammographic Images
Prithul Sarker, Sushmita Sarker, George Bebis +1
Deep learning has made a breakthrough in medical image segmentation in recent years due to its ability to extract high-level features without the need for prior knowledge. In this…