Eric Tan (IMDA) – Scene Understanding for COVID-19

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Abstract

In this session, the speaker will provide an introduction to Digital Services Lab (DSL) of IMDA and share a few Computer Vision related projects that DSL has completed for CoVid-19. The projects include human detection, mask detection and human distance projection. Examples of application and demo will also be presented.

The scene understanding for CoVid-19 is a spin off from the scene understanding for AMRs in commercial buildings. It is mainly about the detection problem in Computer Vision using deep learning. How to make the detection models robust to the dynamic scene environment? What are the challenges, practice and solutions? How are the models being deployed? The speaker will share all these with you.

Towards the closing, the speaker will also share the internship opportunities with DSL.

Speaker’s Profile

Dr Eric Tan is currently an A.I. Scientist with the Digital Services Lab of IMDA. He leads a team of A.I. scientists and engineers in the area of Computer Vision. Prior to joining IMDA, he was a Data Scientist with Consumer Insights & Analytics of MediaCorp. He has more than 15 years experience in A.I. and Machine Learning. In specific, he specialized in large-scale predictive modeling and information retrieval. Award winner and presenter in workshops and conferences. He obtained his Ph.D in Computer Science from City University of Hong Kong.

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