The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Fast Convolutional Sparse Coding
Open accessAbstract
Sparse coding has become an increasingly popular method in learning and vision for a variety of classification, reconstruction and coding tasks. The canonical approach intrinsically assumes independence between observations during learning. For many natural signals however, sparse coding is applied to sub-elements ( i.e. patches) of the signal, where such an assumption is invalid. Convolutional sparse coding explicitly models local interactions through the convolution operator, however the resulting optimization problem is considerably more complex than traditional sparse coding. In this paper, we draw upon ideas from signal processing and Augmented Lagrange Methods (ALMs) to produce a fast algorithm with globally optimal sub problems and super-linear convergence.
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Image Fusion With Convolutional Sparse Representation
Liu, Y., Chen, X., Ward, R. K., & Jane Wang, Z. (2016) · IEEE Signal Processing Letters · doi:10.1109/lsp.2016.2618776 · Cited by 986
Ulyanov, D., Vedaldi, A., & Lempitsky, V. (2020) · International Journal of Computer Vision · doi:10.1007/s11263-020-01303-4 · Cited by 719
Solving inverse problems using data-driven models
Arridge, S., Maass, P., Öktem, O., & Schönlieb, C.-B. (2019) · Acta Numerica · doi:10.1017/s0962492919000059 · Cited by 686
A Comprehensive Study of Activity Recognition Using Accelerometers
Twomey, N., Diethe, T., Fafoutis, X., Elsts, A., McConville, R., Flach, P., & Craddock, I. (2018) · Informatics · doi:10.3390/informatics5020027 · Cited by 143
Fusing multi-scale information in convolution network for MR image super-resolution reconstruction
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Metadata
- Authors
- Bristow, H., Eriksson, A., & Lucey, S.
- Venue
- 2013 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2013-06
- Pages
- 391-398
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2117259536
- Cited by
- 329
- References
- 27
- FWCI
- 35.30
- Type
- conference paper
- Language
- en
- Open access
- green
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- Bristow, H., Eriksson, A., & Lucey, S. (2013). Fast Convolutional Sparse Coding. 2013 IEEE Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.2013.57
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