Cellular neural networks are a remarkable artificial neural network class well suited for real time image processing tasks. In fact, the parallel analogue computing feature makes them really effective in such problems which require a real time response. Moreover, the limited amount of interconnections relative to cell's neighbourhood only, lend themselves to easy VLSI implementation. In previous papers, the authors presented some CNN hardware. Therefore, in this paper, an algorithm for character recognition developed on the 9×9 DPCNN board is presented.
Salerno, M., Sargeni, F., Bonaiuto, V., Favero, F.m. (1998). Multifont character recognition by 9×9 DPCNN board. In Proceedings of 40th Midwest Symposium on Circuits and Systems. Dedicated to the Memory of Professor Mac Van Valkenburg (pp.1338-1341). IEEE - Institute of Electrical and Electronics Engineers Inc. [10.1109/MWSCAS.1997.662329].
Multifont character recognition by 9×9 DPCNN board
SALERNO, MARIO;SARGENI, FAUSTO;BONAIUTO, VINCENZO;
1998-01-01
Abstract
Cellular neural networks are a remarkable artificial neural network class well suited for real time image processing tasks. In fact, the parallel analogue computing feature makes them really effective in such problems which require a real time response. Moreover, the limited amount of interconnections relative to cell's neighbourhood only, lend themselves to easy VLSI implementation. In previous papers, the authors presented some CNN hardware. Therefore, in this paper, an algorithm for character recognition developed on the 9×9 DPCNN board is presented.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
