STAFF PROFILE
Dr. Du Yong Kim
Position:
Lecturer
College / Portfolio:
STEM College
School / Department:
STEM|School of Engineering
Phone:
+61399252634
Email:
duyong.kim@rmit.edu.au
Campus:
City Campus
Contact me about:
Research supervision
- Ong, J.,Vo, B.,Vo, B.,Kim, D.,Nordholm, S. (2022). A Bayesian Filter for Multi-view 3D Multi-object Tracking with Occlusion Handling In: IEEE Transactions on Pattern Analysis and Machine Intelligence, 44, 2246 - 2263
- Ristic, B.,Kim, D.,Rosenberg, L.,Guan, R. (2022). Exploiting Doppler in Bernoulli Track-Before-Detect for a Scanning Maritime Radar In: IEEE Transactions on Aerospace and Electronic Systems, 58, 720 - 728
- Ristic, B.,Guan, R.,Kim, D.,Rosenberg, L. (2022). Bernoulli track-before-detect smoothing for maritime radar In: IET Radar, Sonar and Navigation, 16, 953 - 960
- Ristic, B.,Skvortsov, A.,Arulampalam, S.,Demirhan, H.,Kim, D. (2022). Solving the Datum Search as a Partially Observed Stochastic Game In: IEEE Access, 10, 30762 - 30769
- Kim, D.,Ristic, B.,Guan, R.,Rosenberg, L. (2021). A Bernoulli Track-Before-Detect Filter for Interacting Targets in Maritime Radar In: IEEE Transactions on Aerospace and Electronic Systems, 57, 1981 - 1991
- Ali, A.,Salim, F.,Kim, D.,Neia, A.,Bouguettaya, A. (2021). (In Press) Drone-as-a-Service Composition Under Uncertainty In: IEEE Transactions on Services Computing, , 1 - 14
- Yoon, Y.,Kim, D.,Song, Y.,Yoon, K.,Jeon, M. (2021). Online multiple pedestrians tracking using deep temporal appearance matching association In: Information Sciences, 561, 326 - 351
- Chen, Z.,Ristic, B.,Houssineau, J.,Kim, D. (2021). Observer Control for Bearings-only Tracking Using Possibility Functions In: Automatica, 133, 1 - 7
- Nguyen, T.,Vo, B.,Vo, B.,Kim, D.,Choi, Y. (2021). Tracking Cells and their Lineages via Labeled Random Finite Sets In: IEEE Transactions on Signal Processing, 69, 5611 - 5626
- Kim, D.,Ristic, B.,Rosenberg, L.,Guan, R.,Evans, R. (2021). Exploiting Doppler in Bernoulli Track-Before-Detect In: 2021 IEEE Radar Conference (RadarConf21), Atlanta, GA, USA, 7-14 May 2021
- Drone-based crowd monitoring Qatar National Research Fund Application - DroneCMS: Flying Infrastructure for Intelligent Crowd Management and Security for Mega Events (Administered by Qatar University).. Funded by: Qatar National Research Fund (ONGOING) from (2020 to 2022)
1 PhD Completions and 1 Masters by Research Completions2 PhD Current Supervisions