Patent Document ID: 9953425
Application ID: 14447296
Patent Status: 1

Claim One:
1. A non-transitory computer storage medium comprising computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations comprising: implementing a regularized double-column convolutional neural network (RDCNN) to classify image features for a set of images, the implementing comprising: receiving an image from the set of images; training a first feature column in a first neural network of the RDCNN using a first set of image representations as inputs to the first feature column, the trained first feature column having fixed parameters; generating a first set of image attributes by the trained first feature column using the fixed parameters; and training a second feature multi-column in a second neural network of the RDCNN using the generated first set of image attributes, wherein the parameters of the trained first feature column remain fixed, wherein the second feature multi-column comprises at least two columns that are independent in each convolutional layer of the second feature multi-column, and wherein each of the at least two columns receives a different input; and identifying a class associated with the second feature multi-column for the image using the implemented RDCNN.