AiSLab @ EgoVid presents a demonstration on “deep learning-based activity/fact recognition based on extreme low resolution” at CVPR 2017. [Read More]
A new journal paper, “Optimal Multiuser Diversity in Multi-Cell MIMO Uplink Networks: User Scaling Law and Beamforming Design,” has been accepted by MDPI Entropy (IF: 1.821)
In this project, we study machine learning-based interference management algorithms for interference management in ultra dense network in pursuit of increasing the system throughput while maintaining the signal overhead feasible.
In this project, we study and develop a communication/network system for active mobile trackers working without any extra power source. In the mother project, fundamental technologies underpinning a self-powered miniature nationwide mobile position tracker system are developed. As the third sub-project, we develop wide area sensor communication network systems to support the active trackers.
Myeung Un Kim’s paper, “Min-SINR Maximization with DL SWIPT and UL WPCN in Multi-Antenna Interference Networks,” has been accepted for publication from IEEE Wireless Communications Letters (SCIE, 51/598 of Control and Systems Engineering in SJR Ranking). See here for details.
Hyun Jong Yang founds a startup company, EgoVid Inc. EgoVid studies privacy-preserving (safe) machine learning for signal processing and computer vision. See here.
A new journal paper has been accepted from IEEE Transactions on Wireless Communications (IF: 2.925) [J18]
Hyun Jong Yang gives a talk about ” Machine learning and its applications in communications” in ETRI on Dec. 2016 [T10].
Hyun Jong Yang gives a talk about “Vision and applications of wireless communications” in Postech on Dec. 2016 [T11].
AiSLab visits U. C. Berkeley during the 2016 winter vacation (about 9 weeks) to exchange ideas about making a start-up company.