Titlebook: Document Analysis and Recognition - ICDAR 2023; 17th International C Gernot A. Fink,Rajiv Jain,Richard Zanibbi Conference proceedings 2023

丧失

Critical Approaches to Children‘s Literaturetwork, both in writer-dependent and writer-independent settings. On a large real-world dataset, fine-tuning on new writers provided an average relative CER improvement of 25% for 16 text lines and 50% for 256 text lines.

诗集

PHON

deadlock

Fine-Tuning is a Surprisingly Effective Domain Adaptation Baseline in Handwriting Recognitiontwork, both in writer-dependent and writer-independent settings. On a large real-world dataset, fine-tuning on new writers provided an average relative CER improvement of 25% for 16 text lines and 50% for 256 text lines.

SEEK

向外才掩饰

Improving Handwritten OCR with Training Samples Generated by Glyph Conditional Denoising Diffusion Pve to collect. To mitigate the issue, we propose a denoising diffusion probabilistic model (DDPM) to generate training samples. This model conditions on a printed glyph image and creates mappings between printed characters and handwritten images, thus enabling the generation of photo-realistic handw

震惊

Juvenile

Vision Conformer: Incorporating Convolutions into Vision Transformer LayersViT) adapt transformers for image recognition tasks. In order to do this, the images are split into patches and used as tokens. One issue with ViT is the lack of inductive bias toward image structures. Because ViT was adapted for image data from language modeling, the network does not explicitly han

察觉

抒情短诗

Exploring Semantic Word Representations for Recognition-Free NLP on Handwritten Document Imagesl NLP models constitutes an intuitive solution. However, due to the difficulty of recognizing handwriting and the error propagation problem, optimized architectures are required. Recognition-free approaches proved to be robust, but often produce poorer results compared to recognition-based methods.