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Binary segmentation with neural validation for cursive handwriting recognition

หน่วยงาน Central Queensland University, Australia

รายละเอียด

ชื่อเรื่อง : Binary segmentation with neural validation for cursive handwriting recognition
นักวิจัย : Lee, Hong. , Verma, Brijesh.
คำค้น : Applied research. , 890202 Application Tools and System Utilities. , 080108 Neural, Evolutionary and Fuzzy Computation. , 080109 Pattern Recognition and Data Mining. , Algorithms. , Neural networks (Computer science) , Pattern recognition systems. , Writing , Segmentation algorithm -- Neural networks -- Handwriting recognition
หน่วยงาน : Central Queensland University, Australia
ผู้ร่วมงาน : -
ปีพิมพ์ : 2552
อ้างอิง : http://hdl.cqu.edu.au/10018/45621 , http://dx.doi.org/10.1109/IJCNN.2009.5178955
ที่มา : Lee, H & Verma, B 2009, 'Binary segmentation with neural validation for cursive handwriting recognition' in IEEE editors (eds.) Proceedings of International Joint Conference on Neural Networks. Atlanta, Georgia, USA, June 14-19, 2009, pp. 1730-1735. http://dx.doi.org/10.1109/IJCNN.2009.5178955 (viewed 8/06/10)
ความเชี่ยวชาญ : -
ความสัมพันธ์ : Proceedings of International Joint Conference on Neural Networks, Atlanta, Georgia, USA, June 14-19, 2009. NJ, USA. : IEEE, 2009. p. 1730-1735 6 pages Refereed 1098-7576 (online) 9781424435531 (online) , ACQUIRE [electronic resource] : Central Queensland University Institutional Repository.
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

Over-Segmentation and Validation (OSV) is a well anticipated segmentation strategy in cursive off-line hand writing recognition. Over-Segmentation is a means of locating all possible character boundaries, and the excessive segmentation points called over-segmentation points. Validation is a process to check and validate the segmentation points whether or not they are correct character boundaries by commonly employing an intelligent classifier trained with knowledge of characters. The existing OSV algorithms use ordered validation which means that the incorrect segmentation points might account for the validity of the next segmentation point. The ordered validation creates problems such as chain-failure. This paper presents a novel Binary Segmentation with Neural Validation (BSNV) to reduce the chain-failure. BSNV contains modules of over-segmentation and validation but the main distinctive feature of BSNV is an un-ordered segmentation strategy. The proposed algorithm has been evaluated on CEDAR benchmark database and the results of the experiments are promising.

บรรณานุกรม :
Lee, Hong. , Verma, Brijesh. . (2552). Binary segmentation with neural validation for cursive handwriting recognition.
    กรุงเทพมหานคร : Central Queensland University, Australia.
Lee, Hong. , Verma, Brijesh. . 2552. "Binary segmentation with neural validation for cursive handwriting recognition".
    กรุงเทพมหานคร : Central Queensland University, Australia.
Lee, Hong. , Verma, Brijesh. . "Binary segmentation with neural validation for cursive handwriting recognition."
    กรุงเทพมหานคร : Central Queensland University, Australia, 2552. Print.
Lee, Hong. , Verma, Brijesh. . Binary segmentation with neural validation for cursive handwriting recognition. กรุงเทพมหานคร : Central Queensland University, Australia; 2552.