{"id":4130,"date":"2020-11-26T05:13:42","date_gmt":"2020-11-26T10:13:42","guid":{"rendered":"https:\/\/portfolios.cs.earlham.edu\/?p=4130"},"modified":"2020-11-26T05:13:44","modified_gmt":"2020-11-26T10:13:44","slug":"senior-capstone","status":"publish","type":"post","link":"https:\/\/portfolios.cs.earlham.edu\/index.php\/2020\/11\/26\/senior-capstone\/","title":{"rendered":"Senior Capstone"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">An Integrated Model for Offline Handwritten Chinese Character Recognition Based on Convolutional Neural Networks<\/h2>\n\n\n\n<p><strong>Abstract<\/strong><\/p>\n\n\n\n<p>Optical Character Recognition (OCR) is an important technology in computer vision and pattern recognition that recognizes text embedded in images. Although the OCR achieved high accuracy for languages with alphabet-based writing systems, its performance on handwritten Chinese text is poor due to the complexity of the Chinese writing system. In order to improve the accuracy rate, this paper proposes an integrated OCR model for Chinese handwriting that combines existing methods in the pre-processing phase, recognition phase, and post-processing phase.<\/p>\n\n\n\n<p><a href=\"https:\/\/drive.google.com\/file\/d\/1z-ackF1RNYTDUD3lwj8wXjcC94-2gIYg\/view?usp=sharing\" data-type=\"URL\" data-id=\"https:\/\/drive.google.com\/file\/d\/1z-ackF1RNYTDUD3lwj8wXjcC94-2gIYg\/view?usp=sharing\" target=\"_blank\" rel=\"noreferrer noopener\">Paper<\/a><\/p>\n\n\n\n<p><a href=\"https:\/\/youtu.be\/SYP4UYh4N88\" data-type=\"URL\" data-id=\"https:\/\/youtu.be\/SYP4UYh4N88\" target=\"_blank\" rel=\"noreferrer noopener\">Software Demo Video<\/a><\/p>\n\n\n\n<p><strong>Software Architecture Diagram<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"814\" src=\"https:\/\/portfolios.cs.earlham.edu\/wp-content\/uploads\/2020\/11\/SAD-1024x814.png\" alt=\"\" class=\"wp-image-4131\" srcset=\"https:\/\/portfolios.cs.earlham.edu\/wp-content\/uploads\/2020\/11\/SAD-1024x814.png 1024w, https:\/\/portfolios.cs.earlham.edu\/wp-content\/uploads\/2020\/11\/SAD-300x238.png 300w, https:\/\/portfolios.cs.earlham.edu\/wp-content\/uploads\/2020\/11\/SAD-768x610.png 768w, https:\/\/portfolios.cs.earlham.edu\/wp-content\/uploads\/2020\/11\/SAD.png 1140w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>An Integrated Model for Offline Handwritten Chinese Character Recognition Based on Convolutional Neural Networks Abstract Optical Character Recognition (OCR) is an important technology in computer vision and pattern recognition that recognizes text embedded in images. Although the OCR achieved high &hellip; <a href=\"https:\/\/portfolios.cs.earlham.edu\/index.php\/2020\/11\/26\/senior-capstone\/\">Read More<\/a><\/p>\n","protected":false},"author":90,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[101,119,19],"tags":[],"class_list":["post-4130","post","type-post","status-publish","format-standard","hentry","category-101","category-kate-nguyen","category-student"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Senior Capstone - CS\/DS Student Portfolios<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/portfolios.cs.earlham.edu\/index.php\/2020\/11\/26\/senior-capstone\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Senior Capstone - CS\/DS Student Portfolios\" \/>\n<meta property=\"og:description\" content=\"An Integrated Model for Offline Handwritten Chinese Character Recognition Based on Convolutional Neural Networks Abstract Optical Character Recognition (OCR) is an important technology in computer vision and pattern recognition that recognizes text embedded in images. Although the OCR achieved high &hellip; Read More\" \/>\n<meta property=\"og:url\" content=\"https:\/\/portfolios.cs.earlham.edu\/index.php\/2020\/11\/26\/senior-capstone\/\" \/>\n<meta property=\"og:site_name\" content=\"CS\/DS Student Portfolios\" \/>\n<meta property=\"article:published_time\" content=\"2020-11-26T10:13:42+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2020-11-26T10:13:44+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/portfolios.cs.earlham.edu\/wp-content\/uploads\/2020\/11\/SAD.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1140\" \/>\n\t<meta property=\"og:image:height\" content=\"906\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Kate Nguyen\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Kate Nguyen\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/portfolios.cs.earlham.edu\\\/index.php\\\/2020\\\/11\\\/26\\\/senior-capstone\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/portfolios.cs.earlham.edu\\\/index.php\\\/2020\\\/11\\\/26\\\/senior-capstone\\\/\"},\"author\":{\"name\":\"Kate Nguyen\",\"@id\":\"https:\\\/\\\/portfolios.cs.earlham.edu\\\/#\\\/schema\\\/person\\\/9cf7af838c81ce9f198d67f60da8305a\"},\"headline\":\"Senior Capstone\",\"datePublished\":\"2020-11-26T10:13:42+00:00\",\"dateModified\":\"2020-11-26T10:13:44+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/portfolios.cs.earlham.edu\\\/index.php\\\/2020\\\/11\\\/26\\\/senior-capstone\\\/\"},\"wordCount\":103,\"commentCount\":0,\"image\":{\"@id\":\"https:\\\/\\\/portfolios.cs.earlham.edu\\\/index.php\\\/2020\\\/11\\\/26\\\/senior-capstone\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/portfolios.cs.earlham.edu\\\/wp-content\\\/uploads\\\/2020\\\/11\\\/SAD-1024x814.png\",\"articleSection\":[\"2021\",\"Kate Thuy Nguyen\",\"Student\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\\\/\\\/portfolios.cs.earlham.edu\\\/index.php\\\/2020\\\/11\\\/26\\\/senior-capstone\\\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/portfolios.cs.earlham.edu\\\/index.php\\\/2020\\\/11\\\/26\\\/senior-capstone\\\/\",\"url\":\"https:\\\/\\\/portfolios.cs.earlham.edu\\\/index.php\\\/2020\\\/11\\\/26\\\/senior-capstone\\\/\",\"name\":\"Senior Capstone - 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Although the OCR achieved high &hellip; Read More","_links":{"self":[{"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/posts\/4130","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/users\/90"}],"replies":[{"embeddable":true,"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/comments?post=4130"}],"version-history":[{"count":1,"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/posts\/4130\/revisions"}],"predecessor-version":[{"id":4132,"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/posts\/4130\/revisions\/4132"}],"wp:attachment":[{"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/media?parent=4130"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/categories?post=4130"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/portfolios.cs.earlham.edu\/index.php\/wp-json\/wp\/v2\/tags?post=4130"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}