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

galley

Pharmaceutical Industry Performanceon, spelling correction, and beautification. Writing is personal and usually the processing is done on-device. Ink generative models thus need to produce high quality content quickly, in a resource constrained environment..In this work, we study ways to maximize the quality of the output of a traine

致敬

obsession

GLUT

Translating Samuel Beckett into Hindicognizes 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

Armory

Cirrhosis

Case Study I: Key Concepts and Approachy 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.

Omniscient

帶來(lái)的感覺(jué)

https://doi.org/10.1007/978-3-030-52527-9 area of HTR that has garnered particular interest is the transcription of historical documents, as there is a vast amount of records available that have yet to be processed, potentially resulting in a loss of information due to deterioration..Currently,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

散步

Critical Approaches to Children‘s Literatureethods can be used to adapt a general model to the target dataset. We show that in the case of neural networks trained for handwriting recognition using CTC, simple fine-tuning with data augmentation works surprisingly well in such scenarios and that it is resistant to overfitting even for very smal

Hectic