A hardware polynomial feature net for hand-printed digit recognition

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dc.contributor.author Rao, Arun en_US
dc.contributor.author Anderson, Peter en_US
dc.contributor.author Gaborski, Roger en_US
dc.contributor.author Jaiswal, K.S. en_US
dc.date.accessioned 2006-12-18T17:26:30Z en_US
dc.date.available 2006-12-18T17:26:30Z en_US
dc.date.issued 1993-05-25 en_US
dc.identifier.citation Proceedings of the Third IEE International Conference on Artificial Neural Networks (2003) en_US
dc.identifier.isbn 0-85296-573-7 en_US
dc.identifier.uri http://hdl.handle.net/1850/3090 en_US
dc.description Appears in: Proceedings of the Third IEE International Conference on Artificial Neural Networks, 1993, pp. 36-40. Article is also available online at: http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=6622&arnumber=263261&count=62&index=53 en_US
dc.description.abstract The need for automating the processing of an ever-increasing volume of documents combined with the availability of fast, inexpensive computers has resulted in an explosive growth in documentunderstanding algorithm development. High-volume document-processing applications (such as those required by census and revenue collection organizations) are dominated by a variety of forms. The regions of interest in forms are typically a number of handprinted fields, which must be recognized by a computer and converted to an ASCII code. A number of very successful algorithms have been developed by various researchers (Martin and Pittman (1). LeCun et al. (2). Anderson and Gaborski(3)). and the problem of recognizing isolated, handprinted characters is widely regarded as solved. The potential market for document processing systems makes it desirable to implement character recognition algorithms in low-cost, mass-produceable integrated circuits. This paper describes the hardware implementation of an algorithm which has excellent recognition accuracy and is simple in design. An automatic layout method. performance on a standard data set, SPICE simulation results and quantization issues are discussed. en_US
dc.format.extent 400532 bytes en_US
dc.format.mimetype application/pdf en_US
dc.language.iso en_US en_US
dc.publisher Institute of Electrical and Electronics Engineers (IEEE) en_US
dc.subject Algorithms en_US
dc.subject Character recognition en_US
dc.title A hardware polynomial feature net for hand-printed digit recognition en_US
dc.type Proceedings en_US

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