A parallel-serial recognition cone system for perception: some test results

摘要

This paper presents some results of tests of specific “recognition cone” systems for probabilistic parallel-serial recognition and description of two-dimensional scenes of objects. SIMULA and FORTRAN encoded systems were given particular sets of transforms, and examined for their ability to handle scenes that contain (1) letters, (2) “place-settings” of several pieces of silverware and china and (3) a “real-world” outdoor scene, in color. The same parallel-serial flow through structured layers of variable-resolution probabilistic transforms serves to detect edges, find features, characterize, recognize and describe, without any sharp dividing lines between different types of processes. Thus, a wide variety of diverse sources of information contextually interact, in a relatively simple and general way.