Review on The First Paper on Rectified Linear Units (The Building Block for Current State-of-the-art Deep Convolutional NN)

NORB is a synthetic 3D object recognition dataset that contains five classes of toys (humans, animals, cars, planes, trucks) imaged by a stereo-pair camera system from different viewpoints under different lighting conditions. NORB comes in several versions – the Jittered-Cluttered version has grayscale stereopair images with cluttered background and a central object which is randomly jittered in position, size, pixel intensity etc. There is also a distractor object placed in the periphery. For each class, there are ten different instances, five of which are in the training set and the rest in the test set. So at test time a classifier needs to recognize unseen instances of the same classes.