This is the third part of the VC Dimension and Neural Networks series. This part discusses the important theorems for vc dimension of MLPs.

This is the second part of the VC Dimension and Neural Networks series. This part lists important theorems with proofs and explanations. To know the basics of VC dimension, check Part 1 - VC Dimension.

This is the first part of the VC Dimension and Neural Networks series. Basic definition and some examples of vc dimension of learning algorithms are explained here.

Point Cloud Segmentation is the task for grouping objects or assigning labels to every points in the point cloud. This blog presents different types of methods to perform segmentation.

A Point Cloud is a set of points in 3D space which can represent the boundary or the whole object (including inside points)

Large-Scale Point Cloud Segmentation Network

Loss Functions for Object Detection