The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Fast image scanning with deep max-pooling convolutional neural networks
Abstract
Deep Neural Networks now excel at image classification, detection and segmentation. When used to scan images by means of a sliding window, however, their high computational complexity can bring even the most powerful hardware to its knees. We show how dynamic programming can speedup the process by orders of magnitude, even when max-pooling layers are present.
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Krizhevsky, A. (2024) · doi:10.57702/zp44cu3g · Cited by 23,395
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Ciresan, D., Meier, U., & Schmidhuber, J. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6248110 · Cited by 3,720
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Cited by
Fully convolutional networks for semantic segmentation
Long, J., Shelhamer, E., & Darrell, T. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7298965 · Cited by 38,834
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Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
Chen, L.-C., Zhu, Y., Papandreou, G., Schroff, F., & Adam, H. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01234-2_49 · Cited by 20,054
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Metadata
- Authors
- Giusti, A., Cireşan, D. C., Masci, J., Gambardella, L. M., & Schmidhuber, J.
- Venue
- 2013 IEEE International Conference on Image Processing
- Publisher
- IEEE
- Published
- 2013-09
- Pages
- 4034-4038
- ISSN
- 1522-4880 (ISSN-L)
- OpenAlex
- W2092985495
- Cited by
- 294
- References
- 18
- FWCI
- 12.59
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Giusti, A., Cireşan, D. C., Masci, J., Gambardella, L. M., & Schmidhuber, J. (2013). Fast image scanning with deep max-pooling convolutional neural networks. 2013 IEEE International Conference on Image Processing. https://doi.org/10.1109/icip.2013.6738831
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