Research Fellow, Machine Learning and Visual Data
Application closing date 11/06/2019
Salary £33,199 - £35,210 per annum
Job category/type Research
This research project aims at utilizing existing large-scale RGB domain data to reduce the requirements of IR-domain data (or the other domain data) for general object classification and detection by means of deep domain adaptation technique.
This position provides a unique opportunity to address the problem of domain adaptation and apply to real-world scenarios. The project is hosted by the Centre for Data Science and Scalable Computing (DSSC) in the Institute of Electronics, Communications and Information Technology (ECIT), at Queen's University Belfast, UK and collaborating with Defence Science and Technology Agency (DSTA), Singapore.
With the enormous amount of advancement made by the deeper and broader blending of deep learning methods into computer vision applications, the need of large-scale labelled dataset becomes a significant obstacle every time when a new task is raised. Domain adaptation is a branch in transfer learning where a model that is trained in a source domain is adapted to another target domain. Usually, the source domain is with labelled data while no or limited labelled data are available in the target domain.