Avancerad sökning

Hittade 3 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Recognition of Handwritten Swedish Sentences With Deep Learning

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Hussain Kara Fallah; [2023]
    Nyckelord :;

    Sammanfattning : This study attempts the task of handwritten text recognition within the context of the Swedish language. It examines the applicability of deep neural networks to comprehend handwritten Swedish texts, specifically leveraging the Labors Memory Dataset. LÄS MER

  3. 2. CArDIS: A Swedish Historical Handwritten Character and Word Dataset for OCR

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Shivani Thummanapally; Sakib Rijwan; [2022]
    Nyckelord :Handwritten Text Recognition; Optical Character Recognition; Machine learning methods; historical handwritten character recognition; handwritten character dataset;

    Sammanfattning : Background: To preserve valuable sources and cultural heritage, digitization of handwritten characters is crucial. For this, Optical Character Recognition (OCR) systems were introduced and most widely used to recognize digital characters. LÄS MER

  4. 3. A comparison of OCR methods on natural images in different image domains

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Melvin Lundqvist; Agnes Forsberg; [2020]
    Nyckelord :;

    Sammanfattning : Optical character recognition (OCR) is a blanket term for methods that convert printed or handwritten text into machine-encoded text. As the digital world keeps growing the amount of digital images with text increases, and the need for OCR methods that can handle more than plain text documents as well. LÄS MER