2016
TI-Pooling: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks
CVPR 2016poster
In this paper we present a deep neural network topology that incorporates a simple to implement transformation-invariant pooling operator (TI-pooling). This operator is able to efficiently handle prior knowledge on nuisance variations in the data, such as rotation or scale changes. Most current meth…