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This software was used for producing the simulation results for the paper "Reconstruction Algorithms in Undersampled AFM Imaging", published in IEEE Journal of Selected Topics in Signal Processing: http://dx.doi.org/10.1109/JSTSP.2015.2500363. This deposition consists of a number of Python scripts, some of which were used for producing the results in the accompanying data set available at http://dx.doi.org/10.5281/zenodo.32958 and some of which can be used to extract data and images from said data set. The deposition further contains a README file explaining the purpose and use of the individual files as well as MD5 and SHA checksums of the files for validating the integrity of the files after download. The scripts are licensed under the BSD 2-Clause license (http://opensource.org/licenses/BSD-2-Clause). The scripts perform and analyse results from simulations using images, and reconstructed versions of these, originally published in the data set available at http://dx.doi.org/10.5281/zenodo.17573.
atomic force microscopy, undersampling, sparse approximation, image reconstruction, interpolation, image processing, compressed sensing
atomic force microscopy, undersampling, sparse approximation, image reconstruction, interpolation, image processing, compressed sensing
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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