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

忙碌

OCR Language Models with?Custom Vocabulariespower of language models in this context is the existence of many specialized domains with language statistics very different from those implied by a general language model - think of checks, medical prescriptions, and many other specialized document classes. This paper introduces an algorithm for e

Foregery

設(shè)施

enlist

Linguistic Knowledge Within Handwritten Text Recognition Models: A Real-World Case Studyon layers, which perform recognition over sequences of characters. This architecture may lead to the model learning statistical linguistic features of the training corpus, over and above graphic features. This in turn could lead to degraded performance if the evaluation dataset language differs from

冰雹

過份艷麗

Faster DAN: Multi-target Queries with?Document Positional Encoding for?End-to-End Handwritten Documecognizes the characters one after the other through an attention-based prediction process until reaching the end of the document. However, this autoregressive process leads to inference that cannot benefit from any parallelization optimization. In this paper, we propose Faster DAN, a two-step strate

Chagrin

不足的東西

DSS: Synthesizing Long Digital Ink Using Data Augmentation, Style Encoding and?Split Generationy used models for this task fail to generalize to long-form data and how this problem can be solved by augmenting the training data, changing the model architecture and the inference procedure. These methods use contrastive learning technique and are tailored specifically for the handwriting domain.

動(dòng)機(jī)

Precise Segmentation for?Children Handwriting Analysis by?Combining Multiple Deep Models with?Onlineigh performance for both tasks is necessary to give personalized feedback to children who are learning how to write. The first contribution is to combine the predictions of an accurate Seq2Seq model with the predictions of a R-CNN object detector. The second one is to refine the bounding box predict

輕浮女

Fine-Tuning Vision Encoder–Decoder Transformers for?Handwriting Text Recognition on?Historical Docum area of HTR that has garnered particular interest is the transcription of historical documents, as there is a vast amount of records available that have yet to be processed, potentially resulting in a loss of information due to deterioration..Currently, the most widely used HTR approach is to train