C.-C. Jay Kuo

TL;DR: It is demonstrated by simulation results that the proposed MLE can provide accurate CFO and channel estimation in both SISO and SIMO environments.

TL;DR: A novel hierarchical Bayesian model is proposed which jointly learns activities and group preferences by using topic models; and performs group recommendation using matrix factorization in a collaborative filtering framework and shows that the model provides more effective group recommendation system than the state-of-the-art approaches.

TL;DR: A robust, automated algorithm for unsupervised computer detection of coronary artery lesions that shows promising results in the detection of both obstructive and nonobstructive CCTA lesions.

TL;DR: It is shown that even from unstructured environmental sounds, one can predict with fairly accurate results the type of environment that the robot is positioned, as compared to using visual information alone.

TL;DR: A model-based drone augmentation technique that automatically generates drone images with a bounding box label on drone's location and presents an integrated detection and tracking system that outperforms the performance of each individual module containing detection or tracking only.