Matches in SemOpenAlex for { <https://semopenalex.org/work/W4285141836> ?p ?o ?g. }
Showing items 1 to 82 of
82
with 100 items per page.
- W4285141836 endingPage "101" @default.
- W4285141836 startingPage "91" @default.
- W4285141836 abstract "The goal of recognizing handwritten numbers on paper is to extract the characteristics of the entered handwritten number. The human visual system is one of the wonders of the world. People can easily find and recognize the numbers as they are used for recognition and identification. Most people easily recognize numbers without effort. Humans are amazing at deciphering what our eyes show. All work is done subconsciously, and no additional training is required to recognize numbers. Generally, we do not need to assess the difficulty of a problem that our visual system solves. However, recognizing numbers for mechanical devices such as computers is not that easy. If we try to develop a computer program to detect numbers, the difficulty of visually recognizing patterns is significant. When it comes to coding, what seems simple when we see it will be quite complicated. Simple intuitions, for example, are for a system that recognizes strokes, circles, curves, straight lines, curves, and more. Example of recognizing a number like 9, you should recognize the loop at the top and a straight vertical bar at the bottom right. This is not easy to express algorithmically. That is why we came up with a prototype for number recognition. Although identification, classification and recognition are simple tasks with the help of machine learning, we are trying to develop a system that recognizes numbers as accurately as possible. The main goal of focusing on handwriting recognition is to learn about neural networks. Images are divided into pixels and recognized in pixel order." @default.
- W4285141836 created "2022-07-14" @default.
- W4285141836 creator A5028891181 @default.
- W4285141836 creator A5029227965 @default.
- W4285141836 creator A5039631522 @default.
- W4285141836 creator A5076572193 @default.
- W4285141836 creator A5083915260 @default.
- W4285141836 date "2022-01-01" @default.
- W4285141836 modified "2023-10-16" @default.
- W4285141836 title "An Efficient Novel Approach for Detection of Handwritten Numericals Using Machine Learning Paradigms" @default.
- W4285141836 cites W1964692985 @default.
- W4285141836 cites W2106111846 @default.
- W4285141836 cites W2247605921 @default.
- W4285141836 cites W2596664077 @default.
- W4285141836 cites W2768121648 @default.
- W4285141836 cites W3014849434 @default.
- W4285141836 cites W3033405894 @default.
- W4285141836 cites W3067309663 @default.
- W4285141836 cites W3161605748 @default.
- W4285141836 cites W3185793131 @default.
- W4285141836 cites W3203355104 @default.
- W4285141836 cites W341625861 @default.
- W4285141836 doi "https://doi.org/10.1007/978-3-031-09469-9_8" @default.
- W4285141836 hasPublicationYear "2022" @default.
- W4285141836 type Work @default.
- W4285141836 citedByCount "3" @default.
- W4285141836 crossrefType "book-chapter" @default.
- W4285141836 hasAuthorship W4285141836A5028891181 @default.
- W4285141836 hasAuthorship W4285141836A5029227965 @default.
- W4285141836 hasAuthorship W4285141836A5039631522 @default.
- W4285141836 hasAuthorship W4285141836A5076572193 @default.
- W4285141836 hasAuthorship W4285141836A5083915260 @default.
- W4285141836 hasConcept C105795698 @default.
- W4285141836 hasConcept C111472728 @default.
- W4285141836 hasConcept C116834253 @default.
- W4285141836 hasConcept C119857082 @default.
- W4285141836 hasConcept C138885662 @default.
- W4285141836 hasConcept C153180895 @default.
- W4285141836 hasConcept C154945302 @default.
- W4285141836 hasConcept C160633673 @default.
- W4285141836 hasConcept C179518139 @default.
- W4285141836 hasConcept C2779386606 @default.
- W4285141836 hasConcept C2780586882 @default.
- W4285141836 hasConcept C33923547 @default.
- W4285141836 hasConcept C41008148 @default.
- W4285141836 hasConcept C50644808 @default.
- W4285141836 hasConcept C59822182 @default.
- W4285141836 hasConcept C86803240 @default.
- W4285141836 hasConceptScore W4285141836C105795698 @default.
- W4285141836 hasConceptScore W4285141836C111472728 @default.
- W4285141836 hasConceptScore W4285141836C116834253 @default.
- W4285141836 hasConceptScore W4285141836C119857082 @default.
- W4285141836 hasConceptScore W4285141836C138885662 @default.
- W4285141836 hasConceptScore W4285141836C153180895 @default.
- W4285141836 hasConceptScore W4285141836C154945302 @default.
- W4285141836 hasConceptScore W4285141836C160633673 @default.
- W4285141836 hasConceptScore W4285141836C179518139 @default.
- W4285141836 hasConceptScore W4285141836C2779386606 @default.
- W4285141836 hasConceptScore W4285141836C2780586882 @default.
- W4285141836 hasConceptScore W4285141836C33923547 @default.
- W4285141836 hasConceptScore W4285141836C41008148 @default.
- W4285141836 hasConceptScore W4285141836C50644808 @default.
- W4285141836 hasConceptScore W4285141836C59822182 @default.
- W4285141836 hasConceptScore W4285141836C86803240 @default.
- W4285141836 hasLocation W42851418361 @default.
- W4285141836 hasOpenAccess W4285141836 @default.
- W4285141836 hasPrimaryLocation W42851418361 @default.
- W4285141836 hasRelatedWork W1694630026 @default.
- W4285141836 hasRelatedWork W2027154813 @default.
- W4285141836 hasRelatedWork W2360066868 @default.
- W4285141836 hasRelatedWork W2374694510 @default.
- W4285141836 hasRelatedWork W2381764175 @default.
- W4285141836 hasRelatedWork W2388180914 @default.
- W4285141836 hasRelatedWork W2507888814 @default.
- W4285141836 hasRelatedWork W2561540377 @default.
- W4285141836 hasRelatedWork W3118925046 @default.
- W4285141836 hasRelatedWork W3166464480 @default.
- W4285141836 isParatext "false" @default.
- W4285141836 isRetracted "false" @default.
- W4285141836 workType "book-chapter" @default.