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The focus of this paper is speeding up the evaluation of convolutional neural networks.
ICDAR 2005 text locating competition results
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T. de Campos, B. R. Babu, and M. Varma · 2009
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Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
H. Lee, R. Grosse, R. Ranganath, and A. Y. Ng · 2009
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Large scale mining and retrieval of visual data in a multimodal context
T. Quack · 2009
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Learning convolutional feature hierarchies for visual recognition
K. Kavukcuoglu, P. Sermanet, Y. Boureau, K. Gregor, M. Mathieu, and Y. LeCun · 2010
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A method for text localization and recognition in real-world images
L. Neumann and J. Matas · 2010
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Using text-spotting to query the world
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Large-scale fpga-based convolutional networks
C. Farabet, Y. LeCun, K. Kavukcuoglu, E. Culurciello, B. Martini, P. Akselrod, and S. Talay · 2011
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Text localization in real-world images using efficiently pruned exhaustive search
L. Neumann and J. Matas · 2011
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Are sparse representations really relevant for image classification?
R. Rigamonti, M. A. Brown, and V. Lepetit · 2011
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ICDAR 2011 robust reading competition challenge 2: Reading text in scene images
A. Shahab, F. Shafait, and A. Dengel · 2011
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Segmentation as selective search for object recognition
K. van de Sande, J. Uijlings, T. Gevers, and A. Smeulders · 2011
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Improving the speed of neural networks on cpus
V. Vanhoucke, A. Senior, and M. Z. Mao · 2011
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End-to-end scene text recognition
K. Wang, B. Babenko, and S. Belongie · 2011
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Scene parsing with multiscale feature learning, purity trees, and optimal covers
C. Farabet, C. Couprie, L. Najman, and Y. LeCun · 2012
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Improving neural networks by preventing co-adaptation of feature detectors
G. E. Hinton, N. Srivastava, A. Krizhevsky, I. Sutskever, and R. R. Salakhutdinov · 2012
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ImageNet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Simplifying convnets for fast learning
F. Mamalet and C. Garcia · 2012
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Real-time scene text localization and recognition
Fast training of convolutional networks through ffts
M. Mathieu, M. Henaff, and Y. LeCun · 2013
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Scene text localization and recognition with oriented stroke detection
L. Neumann and J. Matas · 2013
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Learning separable filters
R. Rigamonti, A. Sironi, V. Lepetit, and P. Fua · 2013
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Overfeat: Integrated recognition, localization and detection using convolutional networks
P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun · 2013
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Discriminatively activated sparselets
H. O. Song, T. Darrell, and R. B. Girshick · 2013
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L. Neumann and J. Matas · 2012
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Sparselet models for efficient multiclass object detection
H. O. Song, S. Zickler, T. Althoff, R. Girshick, M. Fritz, C. Geyer, P. Felzenszwalb, and T. Darrell · 2012
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End-to-end text recognition with convolutional neural networks
T. Wang, D. J. Wu, A. Coates, and A. Y. Ng · 2012
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A framework for improved video text detection and recognition
H. Yang, B. Quehl, and H. Sack · 2012
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PhotoOCR: Reading text in uncontrolled conditions
A. Bissacco, M. Cummins, Y. Netzer, and H. Neven · 2013
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Predicting parameters in deep learning
M. Denil, B. Shakibi, L. Dinh, and N. de Freitas · 2013
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Caffe: An open source convolutional architecture for fast feature embedding
Y. Jia · 2013
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A. Toshev and C. Szegedy · 2013
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End-to-End Text Recognition with Hybrid HMM Maxout Models
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Exploiting linear structure within convolutional networks for efficient evaluation
E. Denton, W. Zaremba, J. Bruna, Y. LeCun, and R. Fergus · 2014
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Learning and transferring mid-level image representations using convolutional neural networks
M. Oquab, L. Bottou, I. Laptev, and J. Sivic · 2014
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Cnn features off-the-shelf: an astounding baseline for recognition
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