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Collection of 6,132 images (128 x 128 pixels) cropped from experimental stratigraphy produced in the Tulane Delta Basin, TDB-10-1, under temporally constant boundary conditions. The images are prepared to be used in a machine learning project. Each image is prefixed with a number [0-5] which indicates the strike section the image was selected from. The cropped strike sections are obtained from the archival dataset located on SEN: http://sedexp.net/catalog/tdb-10-1-tulane-delta-basin. After cropping from the strike sections, each image was processed with binarization and a sequence of morphological opening and closing operations. The code that did the processing can be obtained at https://github.com/amoodie/StratGAN/blob/master/process_images/nrand_process.py. This data was produced as part of a larger project: https://github.com/amoodie/StratGAN
machine learning, sedimentology, geomorphology
machine learning, sedimentology, geomorphology
| selected citations These citations are derived from selected sources. 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). | 0 | |
| 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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