141 to 150 of 241 Results
Gzip Archive - 20.6 GB -
MD5: c9efd054e36cd9845021af23dbdde86c
Reconstructed micro-XRCT data set in 16 bit *.tif file format of overview scan "6o" ("6o_projections.tar.gz"). 2940x2940x2141 voxels with a uniform voxel size of 7.5 µm. (Internal ID: 20220818_02/reconstructed) |
Tabular Data - 92.0 MB - 4 Variables, 2710609 Observations - UNF:6:85GK4HNLvPYSdYWASl8Dpw==
Data of the universal testing machine used to apply the axial load sigma_a. |
Tabular Data - 93.7 MB - 4 Variables, 2710606 Observations - UNF:6:gRZCCO845YrgEc9udZcVlg==
Data of the syringe pump used to control the pore fluid pressure p. |
Tabular Data - 81.2 MB - 3 Variables, 2710602 Observations - UNF:6:rdCQ2hRLGvFlsnGmMO4duw==
Data of the syringe pump used to control the confining fluid pressure sigma_r. |
7Z Archive - 417.9 MB -
MD5: ab58b9cb6a76de1e09c5baa790eada71
Data for training and examples for pre/post-processing |
Plain Text - 155 B -
MD5: 770701e71b665603a9e61292c7824135
An example of training log file (all the adopted parameters used during training are saved in this log) |
Python Source Code - 5.7 KB -
MD5: ee7d79e5e2f70aabaae7bae129627301
Post-processing code to create enhanced images |
Python Source Code - 2.4 KB -
MD5: 9b63a89131ad52136b92531a6b7f5e71
Pre-processing code to change the images into available shape and format |
Python Source Code - 7.0 KB -
MD5: 10e1540fe5afda49692b2437eb245903
Training code in order to train the model |
Python Source Code - 17.5 KB -
MD5: 3a13bef31e567313fc8ef766bc00d377
Customized image library in order to save and load the image data |