Part of Advances in Neural Information Processing Systems 8 (NIPS 1995)
Completely parallel object recognition is NP-complete. Achieving a recognizer with feasible complexity requires a compromise be(cid:173) tween parallel and sequential processing where a system selectively focuses on parts of a given image, one after another. Successive fixations are generated to sample the image and these samples are processed and abstracted to generate a temporal context in which results are integrated over time. A computational model based on a partially recurrent feedforward network is proposed and made cred(cid:173) ible by testing on the real-world problem of recognition of hand(cid:173) written digits with encouraging results.