Learning Spatial-Semantic Context with Fully Convolutional Recurrent
Network for Online Handwritten Chinese Text Recognition

Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition

9 October 2016

Lianwen Jin

Papers citing "Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition"

7 / 7 papers shown

Title
2DSig-Detect: a semi-supervised framework for anomaly detection on image data using 2D-signatures Xinheng Xie Kureha Yamaguchi Margaux Leblanc Simon Malzard Varun Chhabra Victoria Nockles Yue-bo Wu AAML 29 0 0 08 Sep 2024
Recognition of Handwritten Chinese Text by Segmentation: A Segment-annotation-free Approach Dezhi Peng Lianwen Jin Weihong Ma C. Xie Hesuo Zhang Shenggao Zhu Jing Li 45 39 0 29 Jul 2022
Feature Engineering with Regularity Structures I. Chevyrev A. Gerasimovičs H. Weber 17 10 0 12 Aug 2021
Improving Attention-Based Handwritten Mathematical Expression Recognition with Scale Augmentation and Drop Attention Zhe Li Lianwen Jin Songxuan Lai Yecheng Zhu 13 45 0 20 Jul 2020
Text Recognition in the Wild: A Survey Xiaoxue Chen Lianwen Jin Yuanzhi Zhu Canjie Luo Tianwei Wang 3DV 23 102 0 07 May 2020
Aggregation Cross-Entropy for Sequence Recognition Zecheng Xie Yaoxiong Huang Yuanzhi Zhu Lianwen Jin Yuliang Liu Lele Xie 17 92 0 17 Apr 2019
A signature-based machine learning model for bipolar disorder and borderline personality disorder Imanol Perez Arribas K. Saunders G. Goodwin Terry Lyons 25 97 0 22 Jul 2017