Survey on Deep Learning-based Kuzushiji Recognition
arXiv:2007.09637
Abstract
Owing to the overwhelming accuracy of the deep learning method demonstrated at the 2012 image classification competition, deep learning has been successfully applied to a variety of other tasks. The high-precision detection and recognition of Kuzushiji, a Japanese cursive script used for transcribing historical documents, has been made possible through the use of deep learning. In recent years, competitions on Kuzushiji recognition have been held, and many researchers have proposed various recognition methods. This study examines recent research trends, current problems, and future prospects in Kuzushiji recognition using deep learning.
References in corpus (10)
- EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
- mixup: Beyond Empirical Risk Minimization
- Deep Residual Learning for Image Recognition
- Random Erasing Data Augmentation
- Data Augmentation using Random Image Cropping and Patching for Deep CNNs
- CenterNet: Keypoint Triplets for Object Detection
- Cascade R-CNN: High Quality Object Detection and Instance Segmentation
- Detecting Text in Natural Image with Connectionist Text Proposal Network
- A human-inspired recognition system for premodern Japanese historical documents
- Automated Transcription for Pre-Modern Japanese Kuzushiji Documents by Random Lines Erasure and Curriculum Learning