Yun-Jung Ku is a Ph.D. student in Electrical and Computer Engineering at University of Florida. She graduated from National Tsing Hua University(Hsinchu, Taiwan) in 2020. Her research interests include Edge Computing, Object Detection, Pose Detection. These days, she has been focusing on projects related to Nividia Jetson and Edge Computing.
2021 IEEE 17th International Conference on eScience Accepted
----- Implement machine learning in data transferring
----- Used picture recognition to improve reservoir forecasting
----- Used Google Coral Dev board to implement Posenet
----- Made Posenet run on ARM64 system
----- Used Edge Computing to implement SunCAVE
----- Combined Recurrent Neural Network and semantic segmentation into Generative Adversarial Networks
----- Used semantic segmentation to find the key object
----- Designed and trained a bidirectional network. Used GANs to produce realistic key object.
         Simultaneously, put others into Recurrent Neural Network to get the super-resolution video
----- Combined feature tracking and keypoint detection on 3D object
----- Designed and trained a network to track the object and keypoints simultaneously
----- Used 3D object detection to produce special effects in post-production
WANC Workshop paper Accepted, is-CANDAR 2019, Japan
----- Used pose detection to get movements of fingers
----- Implemented on smartphones by reducing model complexity and size
----- Designed an App to identify the meaning of sign language with single camera
Introduction to Internet of Things
Computer Vision
Software Studio
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