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Handwritten Text Recognition
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Handwritten Text Recognition (HTR) is the task of automatically identifying and transcribing handwritten text from images or scanned documents into machine-readable text. The goal is to develop a system capable of accurately interpreting diverse handwriting styles, accounting for variations in alignment, stroke, spacing, and noise. This task involves detecting handwritten regions within an image, extracting the text content, and converting it into a structured digital format, enabling further search, indexing, or data analysis.
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Evaluation of HTR models without Ground Truth Material
Continuous Offline Handwriting Recognition using Deep Learning Models
Many Heads but One Brain: Fusion Brain -- a Competition and a Single Multimodal Multitask Architecture
Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes
KOHTD: Kazakh Offline Handwritten Text Dataset
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models
StackMix and Blot Augmentations for Handwritten Text Recognition
Few Shots Are All You Need: A Progressive Few Shot Learning Approach for Low Resource Handwritten Text Recognition
Handling Heavily Abbreviated Manuscripts: HTR engines vs text normalisation approaches
Recurrent neural network transducer for Japanese and Chinese offline handwritten text recognition
Handwritten Digit Recognition using Machine and Deep Learning Algorithms
Enhance to Read Better: A Multi-Task Adversarial Network for Handwritten Document Image Enhancement
LineCounter: Learning Handwritten Text Line Segmentation by Counting
SmartPatch: Improving Handwritten Word Imitation with Patch Discriminators
One-shot Compositional Data Generation for Low Resource Handwritten Text Recognition
TextAdaIN: Paying Attention to Shortcut Learning in Text Recognizers
Rethinking Text Line Recognition Models
MetaHTR: Towards Writer-Adaptive Handwritten Text Recognition
Digital Peter: Dataset, Competition and Handwriting Recognition Methods
Full Page Handwriting Recognition via Image to Sequence Extraction
Urdu Handwritten Text Recognition Using ResNet18
SPAN: a Simple Predict & Align Network for Handwritten Paragraph Recognition
Classification of Handwritten Names of Cities and Handwritten Text Recognition using Various Deep Learning Models
Applications of Machine Learning in Document Digitisation
HANA: A HAndwritten NAme Database for Offline Handwritten Text Recognition
Enhancing Handwritten Text Recognition with N-gram sequence decomposition and Multitask Learning
Sequence-to-Sequence Contrastive Learning for Text Recognition
Have convolutions already made recurrence obsolete for unconstrained handwritten text recognition ?
Recurrence-free unconstrained handwritten text recognition using gated fully convolutional network
Stylometry for Noisy Medieval Data: Evaluating Paul Meyer's Hagiographic Hypothesis
End-to-end Handwritten Paragraph Text Recognition Using a Vertical Attention Network
Boosting offline handwritten text recognition in historical documents with few labeled lines
EASTER: Efficient and Scalable Text Recognizer
OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold
Modified Segmentation Algorithm for Recognition of Older Geez Scripts Written on Vellum
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