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271 to 280 of 457 Results
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
Plain Text - 2.1 KB - MD5: d378b2f2e6e39b343cb17bd2522c6b7d
Detailed description of operation with codes
Python Source Code - 3.8 KB - MD5: c84b9fd76ff97e75a91ccde5cc1395e2
3D U-net model
Gzip Archive - 5.8 MB - MD5: 64a951fccb18c4bd8ce1b022ab0300b7
Raw ultrasonic measurement data in *.csv file format. File name schema: rubber volume fraction of the mixture ("nu"); static preload F_stat. in N ("F"); measurement date. Oscilloscope channels: A = receiver transducer signal; B = transmitter transducer signal.
Gzip Archive - 1.4 GB - MD5: 11861c5baa4155d35b97783e30c7b36f
Projection images (360 deg, angle increment 0.25 deg), dark image (di) and open beam image (ob) in 16 bit *.tif file format. Preload F_stat. = 400 N.
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