NDLI: Handwritten character recognition with sequential convolutional neural network

Content Provider	IEEE Xplore Digital Library
Author	Caihua Liu Jie Liu Fang Yu Yalou Huang Jimeng Chen
Copyright Year	2013
Description	Author affiliation: Coll. of Software, Nankai Univ., Tianjin, China (Fang Yu; Yalou Huang) \|\| Coll. of Inf. Tech. Sci., Nankai Univ., Tianjin, China (Caihua Liu; Jie Liu; Jimeng Chen)
Abstract	Handwritten character recognition has been an active and challenging research problem, due to the large variations of characters and the dependency relationship between characters. Most of traditional methods rarely consider these two challenges simultaneously. This paper proposes a sequential convolutional neural network(CNN) to solve this problem. It considers handwritten words as image sequences and each node of the sequence is an image of a character. A particularly modified convolutional neural network is firstly employed as a trainable feature extractor to extract low-dimensional, linear separable, translationally invariant features. Furthermore, a sequential model, modified conditional random field(CRF), is utilized to model the dependency between characters. Benefiting from the invariant feature learning ability of CNN and structured prediction ability of CRF, the proposed approach boosts the performance over the standard CRF a large margin. Comparing with the state-of-the-art models, our method achieves a better or comparable performance.
Starting Page	291
Ending Page	296
File Size	666339
Page Count	6
File Format	PDF
ISBN	9781479902606
DOI	10.1109/ICMLC.2013.6890483
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Hidden Markov models Abstracts Feature extraction Accuracy Artificial neural networks Conditional Random Field Handwritten Words Recognition Convolutional Neural Network Invariant Features Sequence Models
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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