Proceedings of the Annual Meeting of the Cognitive Science Society

We describe an alternative approach to hand- printed word recognition using a hybrid of proce- dural and connectionist techniques. We utilize two connectionist components: one to concurrently make recognition and segmentation hypotheses, and another to perform refined recognition of segmented characters. Both networks are governed by a pro- cedural controller which incorporates systematic do- main knowledge and procedural algorithms to guide recognition. W e employ an approach wherein an image is pro- cessed over time by a spatiotemporal connectionist network. The scheme offers several attractive fea- tures including shift-invariance and retention of lo- cal spatial relationships along the dimension being temporalized, a reduction in the number of free pa- rameters, and the ability to process arbitrarily long images. Recognition results on a set of real-world isolated ZIP code digits are comparable to the best reported to date, with a 9 6 . 0 % recognition rate and a rate of 9 9 . 0 % w h e n 9.5% of the images are rejected.