Results 51 to 60 of about 2,795 (153)

TILPDeep: A Lightweight Deep Learning Technique for Handwritten Transformed Invariant Pashto Text Recognition

open access: yesIEEE Access, 2023
Pashto is the native language of Afghanistan and one of Pakistan’s most essential and regional languages. The Pashto language has a vast number of native speakers who live in various parts of the world.
Muhammad Shabir   +5 more
doaj   +1 more source

On the Generalization of Handwritten Text Recognition Models

open access: yes2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Recent advances in Handwritten Text Recognition (HTR) have led to significant reductions in transcription errors on standard benchmarks under the i.i.d. assumption, thus focusing on minimizing in-distribution (ID) errors. However, this assumption does not hold in real-world applications, which has motivated HTR research to explore Transfer Learning and
Carlos Garrido-Munoz   +1 more
openaire   +2 more sources

StackMix and Blot Augmentations for Handwritten Text Recognition

open access: yesCoRR, 2021
This paper proposes a handwritten text recognition(HTR) system that outperforms current state-of-the-artmethods. The comparison was carried out on three of themost frequently used in HTR task datasets, namely Ben-tham, IAM, and Saint Gall. In addition, the results on tworecently presented datasets, Peter the Greats manuscriptsand HKR Dataset, are ...
Alex Shonenkov   +4 more
openaire   +2 more sources

A Pix2Pix Architecture for Complete Offline Handwritten Text Normalization

open access: yesSensors
In the realm of offline handwritten text recognition, numerous normalization algorithms have been developed over the years to serve as preprocessing steps prior to applying automatic recognition models to handwritten text scanned images. These algorithms
Alvaro Barreiro-Garrido   +3 more
doaj   +1 more source

Deep Sparse Auto-Encoder Features Learning for Arabic Text Recognition

open access: yesIEEE Access, 2021
One of the most recent challenging issues of pattern recognition and artificial intelligence is Arabic text recognition. This research topic is still a pervasive and unaddressed research field, because of several factors.
Najoua Rahal   +3 more
doaj   +1 more source

Arabic Handwritten Letters Recognition Using Convolutional Neural Networks

open access: yesAdvances in Electrical and Computer Engineering
Arabic handwriting recognition is a complex task due to the script’s cursive nature, the presence of diacritics, character positioning, connected letters, and variations in individual writing styles.
SIDAOUI, B., KAOUAN, M.
doaj   +1 more source

Advancements in CNN Architectures for Offline Handwritten Arabic Character Recognition [PDF]

open access: yesE3S Web of Conferences
Analyzing and classifying images of Arabic handwritten characters is crucial for text understanding and interpretation from image data. The recognition of handwritten Arabic characters not only preserves the integrity of the Arabic language but also ...
El Ibrahimi Aissam   +4 more
doaj   +1 more source

Quo Vadis Handwritten Text Generation for Handwritten Text Recognition?

open access: yes2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
Accepted at ICCV Workshop ...
Vittorio Pippi   +6 more
openaire   +2 more sources

A system for the off-line recognition of handwritten text [PDF]

open access: yesProceedings of the 12th IAPR International Conference on Pattern Recognition (Cat. No.94CH3440-5), 2002
A new system for the recognition of handwritten text is described. The system goes from raw, binary scanned images of census forms to ASCII transcriptions of the fields contained within the forms. The first step is to locate and extract the handwritten input from the forms.
openaire   +1 more source

Curriculum Learning for Handwritten Text Line Recognition [PDF]

open access: yes2014 11th IAPR International Workshop on Document Analysis Systems, 2014
Recurrent Neural Networks (RNN) have recently achieved the best performance in off-line Handwriting Text Recognition. At the same time, learning RNN by gradient descent leads to slow convergence, and training times are particularly long when the training database consists of full lines of text.
Jérôme Louradour   +1 more
openaire   +2 more sources

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