The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Sparse Spatio-spectral Representation for Hyperspectral Image Super-resolution
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Cites
Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000016 · Cited by 17,075
Boyd, S. (2010) · now publishers, Inc. eBooks · doi:10.1561/9781601984616 · Cited by 12,677
Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
Tropp, J. A., & Gilbert, A. C. (2007) · IEEE Transactions on Information Theory · doi:10.1109/tit.2007.909108 · Cited by 9,653
$rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
Aharon, M., Elad, M., & Bruckstein, A. (2006) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2006.881199 · Cited by 9,451
Sparse coding with an overcomplete basis set: A strategy employed by V1?
Olshausen, B. A., & Field, D. J. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00169-7 · Cited by 3,642
Keshava, N., & Mustard, J. F. (2002) · IEEE Signal Processing Magazine · doi:10.1109/79.974727 · Cited by 2,549
Hyperspectral remote sensing data analysis and future challenges
Bioucas-Dias, J. M., Plaza, A., Camps-Valls, G., Scheunders, P., Nasrabadi, N., & Chanussot, J. (2013) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2013.2244672 · Cited by 2,223
Online dictionary learning for sparse coding
Mairal, J., Bach, F., Ponce, J., & Sapiro, G. (2009) · Proceedings of the 26th Annual International Conference on Machine Learning · doi:10.1145/1553374.1553463 · Cited by 2,114
Imaging Spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)
Green, R. O., Eastwood, M. L., Sarture, C. M., Chrien, T. G., Aronsson, M., Chippendale, B. J., Faust, J. A., Pavri, B. E., Chovit, C. J., Solis, M., et al. (1998) · Remote Sensing of Environment · doi:10.1016/s0034-4257(98)00064-9 · Cited by 1,851
Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit
Tropp, J. A., Gilbert, A. C., & Strauss, M. J. (2006) · Signal Processing · doi:10.1016/j.sigpro.2005.05.030 · Cited by 1,347
Cited by
Ghamisi, P., Yokoya, N., Li, J., Liao, W., Liu, S., Plaza, J., Rasti, B., & Plaza, A. (2017) · IEEE Geoscience and Remote Sensing Magazine · doi:10.1109/mgrs.2017.2762087 · Cited by 909
Hyperspectral Image Superresolution by Transfer Learning
Yuan, Y., Zheng, X., & Lu, X. (2017) · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · doi:10.1109/jstars.2017.2655112 · Cited by 267
Metadata
- Authors
- Akhtar, N., Shafait, F., & Mian, A.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2014
- Pages
- 63-78
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2162842940
- Cited by
- 284
- References
- 32
- FWCI
- 29.64
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Sparse Spatio-spectral Representation for Hyperspectral Image Super-resolution. https://app.cochat.ai/papers/10.1007/978-3-319-10584-0_5
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- Akhtar, N., Shafait, F., & Mian, A. (2014). Sparse Spatio-spectral Representation for Hyperspectral Image Super-resolution. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-319-10584-0_5
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
