Trajectory completion via deep learning

Project Member(s): Liu, W.

Funding or Partner Organisation: Southern University of Science and Technology
Southern University of Science and Technology

Start year: 2020

Summary: Deep learning has become prevalent in Intelligent Transportation Systems (ITS). The computers’ increasingly powerful storage and computing capacity guarantee the possibility of the rise of new techniques. Consequently, a considerable part of traditional statistical model and machine learning models have been replaced by deep learning ones. This project studies neural network based missing trajectory completions.

FOR Codes: Pattern Recognition and Data Mining, Information Processing Services (incl. Data Entry and Capture), Deep learning, Information systems, technologies and services not elsewhere classified

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.