Conference item
Deep structured output learning for unconstrained text recognition
- Abstract:
-
We develop a representation suitable for the unconstrained recognition of words in natural images: the general case of no fixed lexicon and unknown length. To this end we propose a convolutional neural network (CNN) based architecture which incorporates a Conditional Random Field (CRF) graphical model, taking the whole word image as a single input. The unaries of the CRF are provided by a CNN that predicts characters at each position of the output, while higher order terms are provided by ano...
Expand abstract
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Authors
Bibliographic Details
- Publisher:
- International Conference on Learning Representations
- Host title:
- International Conference on Learning Representations (ICLR)
- Journal:
- International Conference on Learning Representations More from this journal
- Pages:
- 1-10
- Publication date:
- 2015-05-09
- Acceptance date:
- 2014-12-19
- Event location:
- San Diego
Item Description
- Keywords:
- Pubs id:
-
pubs:678958
- UUID:
-
uuid:542ce865-628c-43b5-b308-595bcb5b7a06
- Local pid:
-
pubs:678958
- Source identifiers:
-
678958
- Deposit date:
-
2017-02-09
Terms of use
- Copyright date:
- 2015
Metrics
If you are the owner of this record, you can report an update to it here: Report update to this record