Handwriting recognition using high performance computing platforms
Investigation on the feasibility of various character features extracted for handwritten character recognition are comprehensively benchmarked and many variants classifiers using neural network technologies are described. Extensive coverage of preprocessing techniques are listed and illustrated. Neu...
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
2009
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| Online Access: | http://hdl.handle.net/10356/20433 |
| _version_ | 1826115385219350528 |
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| author | Chan, Khue Hiang. |
| author2 | Ng, Geok See |
| author_facet | Ng, Geok See Chan, Khue Hiang. |
| author_sort | Chan, Khue Hiang. |
| collection | NTU |
| description | Investigation on the feasibility of various character features extracted for handwritten character recognition are comprehensively benchmarked and many variants classifiers using neural network technologies are described. Extensive coverage of preprocessing techniques are listed and illustrated. Neural network technologies in particular, the backpropagation neural network are extensively reviewed and studied in the context of learning problems in handwriting recognition. The use of post-processor techniques and multi-neural network architectures in character recognition are also presented. |
| first_indexed | 2024-10-01T03:54:17Z |
| format | Thesis |
| id | ntu-10356/20433 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:54:17Z |
| publishDate | 2009 |
| record_format | dspace |
| spelling | ntu-10356/204332020-09-27T20:15:17Z Handwriting recognition using high performance computing platforms Chan, Khue Hiang. Ng, Geok See School of Applied Science DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition Investigation on the feasibility of various character features extracted for handwritten character recognition are comprehensively benchmarked and many variants classifiers using neural network technologies are described. Extensive coverage of preprocessing techniques are listed and illustrated. Neural network technologies in particular, the backpropagation neural network are extensively reviewed and studied in the context of learning problems in handwriting recognition. The use of post-processor techniques and multi-neural network architectures in character recognition are also presented. Master of Applied Science 2009-12-15T02:59:32Z 2009-12-15T02:59:32Z 1997 1997 Thesis http://hdl.handle.net/10356/20433 en NANYANG TECHNOLOGICAL UNIVERSITY 236 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition Chan, Khue Hiang. Handwriting recognition using high performance computing platforms |
| title | Handwriting recognition using high performance computing platforms |
| title_full | Handwriting recognition using high performance computing platforms |
| title_fullStr | Handwriting recognition using high performance computing platforms |
| title_full_unstemmed | Handwriting recognition using high performance computing platforms |
| title_short | Handwriting recognition using high performance computing platforms |
| title_sort | handwriting recognition using high performance computing platforms |
| topic | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition |
| url | http://hdl.handle.net/10356/20433 |
| work_keys_str_mv | AT chankhuehiang handwritingrecognitionusinghighperformancecomputingplatforms |