Deeply Semantic Inductive Spatio-Temporal Learning
Jakob Suchan, Mehul Bhatt, Carl Peter Leslie Schultz · arXiv (Cornell University) · 2016
We present an inductive spatio-temporal learning framework rooted in inductive logic programming. With an emphasis on visuo-spatial language, logic, and cognition, the framework supports learning with relational spatio-temporal features identifiable in a range of domains involving the processing and interpretation of dynamic visuo-spatial imagery. We present a prototypical system, and an example application in the domain of computing for visual arts and computational cognitive science.