1. A method comprising: training a collection of multiclass convolutional neural networks (CNNs) via a boosting process comprising at least one boost iteration to utilize an auxiliary CNN, the auxiliary CNN to form an ensemble with the collection as a linear combination, the linear combination based at least in part on boost prediction error encountered during the training process with a subset of the collection.