Jean is a PhD student in the Department of Electrical Engineering and Computer Science (EECS) at the University of Michigan, Ann Arbor.
She is advised by Prof. Walter S. Lasecki in EECS.
Her research interest spans digital image processing, human-computer interaction (HCI), machine learning and crowdsourcing.
She was previously coadvised by Prof. (Emeritus) Charles R. Meyer in the Department of Biomedical Engineering and Prof. Jeffrey A. Fessler in EECS.
She is looking for internships in related fields such as computer vision and HCI.
We are building crowdsourcing tools to help autonomous robots recognize new contexts or problems in real-time.
Our system uses a hybrid intelligent workflow that combines human intelligence from the crowd with automated
support in the form of focused tasks (ones that the system is not able to complete on its own) and smart tools
for aiding object segmentation. This uses the machine’s ability to precisely select content with people’s semantic
understanding of the scene. It also allows us to benefit from as much automated labeling as can be done reliably,
while using human intelligence to both fill in the gaps, and ensure that new objects in a scene do not result
in failures to complete an assigned task.
Intermodal Non-rigid Image Registration
Previously I worked on image registration stuffs such as intermodal non-rigid image registration based on mutual information and 2D-3D projection image registration.
- Jean Y. Song and Charles R. Meyer, 2D-3D Image Registration using Thin-Plate Spline and Volume Rendering,
SPIE Medical Imaging 2015, Orlando, Feb. 2015. (poster)
- Jean Y. Song, J. A. Fessler, and C. R. Meyer, Adaptive Filtering on Conditional Mutual Information for
Intermodal Non-Rigid Image Registration, IEEE NSS/MIC 2014, Seattle, Nov. 2014. (poster)