Title :
Deeply embedded handwriting recognition
Author :
Hervieu, Marc ; Brunel, JeanYves
Author_Institution :
Lab. d´´Electron. Philips, Limeil-Brevannes, France
Abstract :
The PHRASES system described generates handwriting recognizers to fit on one chip with the embedded processor of a personal digital assistant. It resorts to an artificial neural network symbol classifier that is backed up by a dictionary search at word level. It uses the chip-synthesis ALMA methodology to produce embeddable implementations which are tuned to application specific requirements such as the resolution of the input tablet or the dictionary size
Keywords :
application specific integrated circuits; handwriting recognition; neural chips; notebook computers; real-time systems; PHRASES system; artificial neural network; chip-synthesis ALMA methodology; deeply embedded handwriting recognition; dictionary search; dictionary size; embeddable implementations; input tablet; personal digital assistant; symbol classifier; Application specific integrated circuits; Artificial neural networks; Computer architecture; Dictionaries; Embedded system; Handwriting recognition; Network synthesis; Personal digital assistants; Power generation; Synchronous generators;
Conference_Titel :
ASIC Conference and Exhibit, 1994. Proceedings., Seventh Annual IEEE International
Conference_Location :
Rochester, NY
Print_ISBN :
0-7803-2020-4
DOI :
10.1109/ASIC.1994.404560
