INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Handwritten text recognition is a challenging task in the field of pattern recognition and artificial intelligence. This research paper proposes a novel approach for intelligent handwritten text recognition by integrating a hybrid architecture of Convolutional Neural Network (CNN) and Support Vector Machine (SVM) classifier with dropout regularization. These identification algorithms must overcome various obstacles, including as vast open data-bases, an endless range of handwriting styles, and freestyle The authors have also put forth a ground-breaking depth neural network training rule for maximum interval minimal classification error in light of the analysis of the error backpropagation method. On the databases AHDB, AHCD, HACDB, and IFN/ENIT, authors tested the suggested model.
Keywords:
Deep Learning,CNN,SVM,M3CE,ZCA
Cite Article:
"INTELLIGENT HANDWRITTEN TEXT RECOGNITION USING HYBRID CNN ARCHITECTURE BASED SVM CLASSIFIER WITH DROPOUT ", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.f466-f469, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305571.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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