Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/547599
Title: Analysis of deep learning architectures for dysgraphia identification and classification using handwritten text images
Researcher: Devi, A
Guide(s): 
Keywords: architectures
dysgraphia
Engineering
Engineering and Technology
Engineering Electrical
handwritten
University: Anna University
Completed Date: 2023
Pagination: xxi,177p.
URI: http://hdl.handle.net/10603/547599
Appears in Departments:Faculty of Electrical Engineering

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01_title.pdfAttached File24.55 kBAdobe PDFView/Open
02_prelim pages.pdf1.88 MBAdobe PDFView/Open
03_content.pdf38.57 kBAdobe PDFView/Open
04_abstract.pdf31.81 kBAdobe PDFView/Open
05_chapter 1.pdf463.39 kBAdobe PDFView/Open
06_chapter 2.pdf282.76 kBAdobe PDFView/Open
07_chapter 3.pdf410.51 kBAdobe PDFView/Open
08_chapter 4.pdf958.63 kBAdobe PDFView/Open
09_chapter 5.pdf937.98 kBAdobe PDFView/Open
10_chapter 6.pdf1.17 MBAdobe PDFView/Open
11_chapter 7.pdf50.13 kBAdobe PDFView/Open
12_annexures.pdf136.23 kBAdobe PDFView/Open
80_recommendation.pdf79.54 kBAdobe PDFView/Open
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