ADR Awareness Centre

Image understanding benefits from the modeling of knowledge about both the scene observed and the objects it contains as well as their relationships.

There is an issue of domain shift in machine learning models, which occurs when models trained on one dataset perform poorly when tested on data from a different source.

In the past decade, artificial intelligence has made remarkable progress, achieving feats like self-driving cars, defeating go-masters, and precise image categorisation through supervised deep learning with labelled data.

The acquisition and self-improvement of novel motor skills is among the most important problems in robotics.

The aim of this lecture is to a) define Computational Politics as a discipline lying at the intersection of Political science and Computer science and b) present the use of AI and IT tools in political data analysis.

Stereoscopic and multiview imaging will be explored in depth, as they have tremendous applications in many applications, ranging from autonomous car/drone/robot/vessel vision to Surveying Engineering to Medical Imaging.