1. A computer-implemented method for training an object-recognition neural network to identify an object in a computer-readable image, the method comprising: assigning, using a processor system, a first neural network for determining a visual alignment model of a plurality of input images, wherein the visual alignment model is used to determine a normalized alignment of an object in the input images; assigning, using the processor system, a second neural network for determining a visual representation model of the input images, wherein the visual representation model is used to recognize the object in the input images; determining the visual alignment model by training the first neural network; determining the visual representation model by training the second neural network; determining a combined object recognition model by training a combination of neural networks comprising the first neural network and the second neural network; and recognizing the object in the computer-readable image based on the combined object recognition model by passing the computer-readable image through the first neural network and the second neural network of the combination of neural networks.