Systems and Methods for Deep Model Translation Generation

A method for improving the training of a computer-based object recognizer to recognize an object within an image, the method comprising:

• (a) obtaining a set of real-world images of a target object;
• (b) creating a set of synthetic images of the target object;
• (c) training a translator to produce a plurality of translated images of the target object, said translator comprising a first computer-based machine learning system having a convolutional autoencoder, where said translator training includes providing the translator with a plurality of pairings, where each pairing is obtained by identifying one of the set of real-world images that corresponds with one of the set of synthetic images, and where the convolutional autoencoder learns from the pairings how to produce the plurality of translated images of the target object;
• (d) invoking the trained translator to produce the plurality of translated images;
• (e) training a generative adversarial network (GAN) to produce a plurality of generated images of the target object, said GAN comprising a second computer-based machine learning system having a discriminative neural network and a generative neural network, where said GAN training includes instantiating the generative neural network with Gaussian noise and instantiating the discriminative neural network with the set of real-world images, where each image in the set of real-world images is labeled according to the target object;
• (f) invoking the trained GAN to produce the plurality of generated images;
• (g) training an object recognizer to recognize the target object within a newly presented digital image by providing the object recognizer a collection of training images, said collection of training images assembled from (1) the set of real-world images of the target object, (2) the plurality of translated images of the target object, and (3) the plurality of generated images of the target object, said object recognizer embodied in at least a portion of a high-speed graphics processing unit of a digital computer, said object recognizer comprising a machine learning module capable of being trained with the collection of training images to recognize the target object within the newly presented digital image;
• and
• (h) using the trained object recognizer to recognize the target object in the new digital image, where the new digital image is obtained from an external image sensor.