A framework is presented which uses a polar representation of a segmented object for shape classification. This method produces a position, rotation and scale invariant representation of the shape. An ...

Introduction This project demonstrates the use of Graph Neural Networks (GNNs) to classify synthetic 2D shapes (triangles, rectangles, circles, hexagons, ellipses). It covers the full machine learning ...