Results 61 to 70 of about 79,075 (205)

Metrics and Models for Handwritten Character Recognition [PDF]

Statistical Science, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hastie, Trevor, Simard, Patrice Y.
openaire   +3 more sources

Learning Based Ge'ez Character Handwritten Recognition

2024 IEEE International Multi-Conference on Smart Systems & Green Process (IMC-SSGP)
Ge'ez, an ancient Ethiopic script of cultural and historical significance, has been largely neglected in handwriting recognition research, hindering the digitization of valuable manuscripts. Our study addresses this gap by developing a state-of-the-art Ge'ez handwriting recognition system using Convolutional Neural Networks (CNNs) and Long Short-Term ...
Yimer, Hailemicael Lulseged, Degefa, Hailegabriel Dereje, Cristani, Marco, Cunico, Federico   +3 more
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On Georgian Handwritten Character Recognition

IFAC-PapersOnLine, 2018
Abstract The article addresses the issue of Georgian handwritten text recognition. As a result of the performed research activity, a framework for recognizing handwritten Georgian text using Self-Normalizing Convolutional Neural Networks (CNN) was developed. To train the CNN model, an extensive dataset was created with over 200 000 character samples.
Davit Soselia, Magda Tsintsadze, Levan Shugliashvili, Irakli Koberidze, Shota Amashukeli, Sandro Jijavadze   +5 more
openaire   +1 more source

Towards Robust Recognition of Handwritten Arabic Characters with Diacritics Using an Incremental Learning Approach Based on CNNs

Emitter: International Journal of Engineering Technology
Handwritten Arabic text recognition (HATR) presents unique challenges due to complex character shapes, contextual variations, cursive connections, and the presence of diacritical marks.
Fatima Aliyu Shugaba, Usman Ullah Sheikh, Mohd Afzan Othman, Nurulaqilla Khamis, Muhammad Habibullah Abdulfattah   +4 more
doaj   +1 more source

A New Deep Learning-Based Handwritten Character Recognition System on Mobile Computing Devices

Journal on spesial topics in mobile networks and applications, 2019
Deep learning (DL) is a hot topic in current pattern recognition and machine learning. DL has unprecedented potential to solve many complex machine learning problems and is clearly attractive in the framework of mobile devices.
Yu Weng, Chunlei Xia
semanticscholar   +1 more source

Lampung handwritten character recognition

, 2016
Lampung script is a local script from Lampung province Indonesia. The script is a non-cursive script which is written from left to right. It consists of 20 characters. It also has 7 unique diacritics that can be put on top, bottom, or right of the character. Considering this position, the number of diacritics augments into 12 diacritics.
openaire   +2 more sources

Handwritten Character Recognition System

Journal of Electrical Systems
Digitizing handwritten documents and enabling efficient information processing and retrieval require systems that can recognize handwritten characters. This research offers a unique approach for handwritten character detection using state-of-the-art machine learning algorithms.
openaire   +1 more source

Benchmarking on offline Handwritten Tamil Character Recognition using convolutional neural networks

Journal of King Saud University: Computer and Information Sciences, 2019
Convolutional Neural Networks (CNN) are playing a vital role nowadays in every aspect of computer vision applications. In this paper we have used the state of the art CNN in recognizing handwritten Tamil characters in offline mode.
B. R. Kavitha, C. Srimathi
semanticscholar   +1 more source

Incomplete handwritten Dongba character image recognition by multiscale feature restoration

Heritage Science
Incomplete handwritten Dongba character often appears in heritage documents and its recognition is significant for heritage and philology. However, all previous methods always suppose that a complete Dongba character is used as input, and thus fail to ...
Xiaojun Bi, Yanlong Luo
doaj   +1 more source

Multi-Attention Based Convolutional Neural Network for Tamil Handwritten Character Recognition

IEEE Access
The robustness of a handwritten character recognition system hinges on its ability to generalize across diverse handwriting styles, especially in regional scripts like Tamil, which are known for their complex curves and structural intricacies.
Srinithi Jayachandran, Yakesh Selvakumar, S. Anubha Pearline   +2 more
doaj   +1 more source