Combining Convolutional Neural Networks and LSTMs for Segmentation-Free OCR

被引：12

作者：

Rawls, Stephen ^{[1
]}

Cao, Huaigu ^{[1
]}

Kumar, Senthil ^{[1
]}

Natarajan, Prem ^{[1
]}

机构：

[1] Univ Southern Calif, Informat Sci Inst, Los Angeles, CA 90007 USA

来源：

2017 14TH IAPR INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION (ICDAR), VOL 1 | 2017年

关键词：

D O I：

10.1109/ICDAR.2017.34

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present a novel end-to-end trainable OCR system combining a CNN for feature extraction with 1-D LSTMs for sequence modeling. We present results on English and Arabic handwriting data, and on English machine print data, showing state-of-the-art performance. We believe that our method is simpler than existing 2D LSTM models, and will make it easier to use techniques borrowed from CNN research in computer vision to improve OCR performance.

引用

页码：155 / 160

页数：6

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