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Physical Sciences and Mathematics Commons

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Medicine and Health Sciences

Singapore Management University

Covid-19

Publication Year

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

Self-Supervised Pseudo Multi-Class Pre-Training For Unsupervised Anomaly Detection And Segmentation In Medical Images, Yu Tian, Fengbei Liu, Guansong Pang, Yuanhong Chen, Yuyuan Liu, Johan W. Verjans, Rajvinder Singh, Gustavo Carneiro Dec 2023

Self-Supervised Pseudo Multi-Class Pre-Training For Unsupervised Anomaly Detection And Segmentation In Medical Images, Yu Tian, Fengbei Liu, Guansong Pang, Yuanhong Chen, Yuyuan Liu, Johan W. Verjans, Rajvinder Singh, Gustavo Carneiro

Research Collection School Of Computing and Information Systems

Unsupervised anomaly detection (UAD) methods are trained with normal (or healthy) images only, but during testing, they are able to classify normal and abnormal (or disease) images. UAD is an important medical image analysis (MIA) method to be applied in disease screening problems because the training sets available for those problems usually contain only normal images. However, the exclusive reliance on normal images may result in the learning of ineffective low-dimensional image representations that are not sensitive enough to detect and segment unseen abnormal lesions of varying size, appearance, and shape. Pre-training UAD methods with self-supervised learning, based on computer …


Covid-19 One Year On: Security And Privacy Review Of Contact Tracing Mobile Apps, Wei Yang Ang, Lwin Khin Shar Oct 2021

Covid-19 One Year On: Security And Privacy Review Of Contact Tracing Mobile Apps, Wei Yang Ang, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

The ongoing COVID-19 pandemic caused 3.8 million deaths since December 2019. At the current vaccination pace, this global pandemic could persist for several years. Throughout the world, contact tracing (CT) apps were developed, which play a significant role in mitigating the spread of COVID-19. This work examines the current state of security and privacy landscape of mobile CT apps. Our work is the first attempt, to our knowledge, which provides a comprehensive analysis of 70 CT apps used worldwide as of year Q1 2021. Among other findings, we observed that 80% of them may have handled sensitive data without adequate …