Htr for greek historical handwritten documents
L Tsochatzidis, S Symeonidis, A Papazoglou… - Journal of …, 2021 - mdpi.com
Offline handwritten text recognition (HTR) for historical documents aims for effective
transcription by addressing challenges that originate from the low quality of manuscripts …
transcription by addressing challenges that originate from the low quality of manuscripts …
Best practices for a handwritten text recognition system
Handwritten text recognition has been developed rapidly in the recent years, following the
rise of deep learning and its applications. Though deep learning methods provide notable …
rise of deep learning and its applications. Though deep learning methods provide notable …
Self-training of handwritten word recognition for synthetic-to-real adaptation
Performances of Handwritten Text Recognition (HTR) models are largely determined by the
availability of labeled and representative training samples. However, in many application …
availability of labeled and representative training samples. However, in many application …
Self-Training-Transductive-Learning Broad Learning System (STTL-BLS): A model for effective and efficient image classification
L Yi, D Lv, D Liu, S Li, R Liu - Pattern Recognition, 2024 - Elsevier
A novel model called Self-Training-Transductive-Learning Broad Learning System (STTL-
BLS) is proposed for image classification. The model consists of two key blocks: Feature …
BLS) is proposed for image classification. The model consists of two key blocks: Feature …
Self-training for handwritten word recognition and retrieval
Handwritten text recognition and Word Retrieval, also known as Word Spotting, are
traditional problems in the document analysis community. While the use of increasingly …
traditional problems in the document analysis community. While the use of increasingly …
A New Optimization Approach to Improve an Ensemble Learning Model: Application to Persian/Arabic Handwritten Character Recognition
Due to the advancement of technology, handwriting recognition has become more important
than ever. As a result, several methods for document image recognition have been …
than ever. As a result, several methods for document image recognition have been …
Shared-Operation Hypercomplex Networks for Handwritten Text Recognition
Parameterized hypercomplex layers have recently emerged as very useful alternatives of
standard neural network layers. They allow for the construction of extremely lightweight …
standard neural network layers. They allow for the construction of extremely lightweight …
Combining self-training and minimal annotations for handwritten word recognition
Abstract Handwritten Text Recognition (HTR) relies on deep learning to achieve high
performances. Its success is substantially driven by large annotated training datasets …
performances. Its success is substantially driven by large annotated training datasets …