Simulated neural circuitry is trained using sequences of images representing moving objects, such that the simulated neural circuitry recognizes objects by having the presence of lower level object features that occurred in temporal sequence in the images representing moving objects trigger the activation of higher level object representations. Thereafter, an image of an object that includes lower level object features is received, the trained simulated neural circuitry activates a higher level representation of the object in response to the lower level object features from the image, and the object is recognized using the trained simulated neural circuitry.
Invariant object recognition