Recent years have witnessed the growing pervasiveness of intelligent video surveillance (VS) systems due to significant advancements of both deep learning and edge computing technologies. On one hand, deep learning has transformed VS systems into authentic visual intelligence ecosystems capable of detecting, recognizing and tracking objects of interest. On the other hand, edge computing (EC) offloads the computational burden from the network center to the edge of the network in order to minimize huge communication overhead. This project aims to optimize the network bandwidth utilization while maximizing the number of query-specified objects from multi-camera wireless video feeds.
Monthly stipend: Up to RM 3,000 (Depending on Qualifications and Experience)
MEng/MSc or BEng/BSc (First Class Honours) in a field related to Electrical, Electronic, Telecommunications Engineering, Computer Science
Physical Layer Signal Processing
Software: MATLAB, Caffe/TensorFlow (Linux)
Excellent command of English
Able to work with minimal supervision, self-motivated and independent
Good track records in journal publications
Publications in ISI Journals and Top Conference Proceedings
Only shortlisted applicants will be notified and called for interview.