Easter2.0: Improving convolutional models for handwritten text recognition [PDF]
arXiv.org, 2022 Convolutional Neural Networks (CNN) have shown promising results for the task of Handwritten Text Recognition (HTR) but they still fall behind Recurrent Neural Networks (RNNs)/Transformer based models in terms of performance.
Kartik Chaudhary, Raghav Bali
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The Challenges of Recognizing Offline Handwritten Chinese: A Technical Review
Applied Sciences, 2023 Offline handwritten Chinese recognition is an important research area of pattern recognition, including offline handwritten Chinese character recognition (offline HCCR) and offline handwritten Chinese text recognition (offline HCTR), which are closely ...
Lu Shen +5 more
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HTR-VT: Handwritten text recognition with vision transformer [PDF]
Pattern RecognitionWe explore the application of Vision Transformer (ViT) for handwritten text recognition. The limited availability of labeled data in this domain poses challenges for achieving high performance solely relying on ViT.
Yuting Li +3 more
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MetaHTR: Towards Writer-Adaptive Handwritten Text Recognition [PDF]
Computer Vision and Pattern Recognition, 2021 Handwritten Text Recognition (HTR) remains a challenging problem to date, largely due to the varying writing styles that exist amongst us. Prior works however generally operate with the assumption that there is a limited number of styles, most of which ...
A. Bhunia +5 more
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Generative adversarial network based adaptive data augmentation for handwritten Arabic text recognition [PDF]
PeerJ Computer Science, 2022 Training deep learning based handwritten text recognition systems needs a lot of data in terms of text images and their corresponding annotations. One way to deal with this issue is to use data augmentation techniques to increase the amount of training ...
Mohamed Eltay +3 more
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On developing handwritten character image database for Malayalam language script
Engineering Science and Technology, an International Journal, 2019 The objective of this paper is to build a handwritten character image database for Malayalam language script. Standard handwritten document image databases are an essential requirement for the development and objective evaluation of different handwritten
K. Manjusha, M. Anand Kumar, K.P. Soman
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AHWR-Net: offline handwritten amharic word recognition using convolutional recurrent neural network
SN Applied Sciences, 2021 Amharic ( ) is the official language of the Federal Government of Ethiopia, with more than 27 million speakers. It uses an Ethiopic script, which has 238 core and 27 labialized characters. It is a low-resourced language, and a few attempts have been made
Fetulhak Abdurahman +2 more
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Real-Time Pashto Handwritten Character Recognition Using Salient Geometric and Spectral Features
IEEE Access, 2021 Pashto scripts are cursive in nature and hard to recognize in real-time. Native speakers of the Pashto language are large in numbers and reside in different regions of the world.
Muhammad Shabir +8 more
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Few shots are all you need: A progressive learning approach for low resource handwritten text recognition [PDF]
Pattern Recognition Letters, 2021 Handwritten text recognition in low resource scenarios, such as manuscripts with rare alphabets, is a challenging problem. The main difficulty comes from the very few annotated data and the limited linguistic information (e.g.
Mohamed Ali Souibgui +3 more
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Handwriting-Based Text Line Segmentation from Malayalam Documents
Applied Sciences, 2023 Optical character recognition systems for Malayalam handwritten documents have become an open research area. A major hindrance in this research is the unavailability of a benchmark database. Therefore, a new database of 402 Malayalam handwritten document
Pearlsy P V, Deepa Sankar
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