551 to 560 of 862 Results
Jan 16, 2022 -
UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images
Plain Text - 5.5 KB -
MD5: 8ea32d6fc6608c9bb88f3f58393234ff
README |
Jan 16, 2022 -
UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images
ZIP Archive - 466.9 MB -
MD5: 0e3491e2653da38cb1b3c73146a6cdad
Random forest based bright-field image cell segmentation model as Ilastik model |
Jan 16, 2022 -
UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images
Unknown - 1022.6 MB -
MD5: aa0b7ff5cf8f238c870cd2ab01567ba5
Random forest based bright-field image cell segmentation model as Ilastik model |
Jan 16, 2022 -
UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images
ZIP Archive - 154.0 MB -
MD5: 909c653b0327db87759cd487debadda0
Random forest based fluorescence image cell segmentation model as Ilastik model |
Jan 16, 2022 -
UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images
ZIP Archive - 13.7 MB -
MD5: 56fb5e9106cbfbb35df1a1ba7336825e
U-Net3 based bright-field image cell segmentation model as Keras model |
Jan 16, 2022 -
UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images
ZIP Archive - 14.2 MB -
MD5: 1a1aecbbb79cb68beeb6fbf9b6e0f011
U-Net3 based fluorescence image cell segmentation model as Keras model |
Jan 16, 2022 - Keemia instituudi andmed
Tahk, Maris-Johanna; Torp, Jane; Ali, Mohammed A.S.; Fishman, Dmytro; Parts, Leopold; Grätz, Lukas; Müller, Christoph; Keller, Max; Veiksina, Santa; Laasfeld, Tõnis; Rinken, Ago, 2022, "UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth", https://doi.org/10.23673/RE-305, DATADOI, V1
The "UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth" dataset contains the raw microscopy images, corresponding bright-field Z-stack based contrast-enhanced images and the corresponding manual ground truth for fluorescence and bright-field images as well as ground truth generated from... |
Jan 16, 2022 -
UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth
ZIP Archive - 514.9 MB -
MD5: dfe14ab180619c2c1257079dd38de63c
Images used for training Ilastik random forest models |
Jan 16, 2022 -
UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth
HTML - 907 B -
MD5: c07b6daef3dbee864bf87e6aa836cde2
2026. aasta migratsiooni käigus varasemast DataDOI süsteemist üle kantud kasutusstatistika kajastab tegevust eelmises DSpace-põhises süsteemis ega näita Dataverse’i uusi kasutusandmeid.
Usage statistics carried over from the previous DataDOI system as part of the 2026 migration reflect activity in the former DSpace-based system and do not represent... |
Jan 16, 2022 -
UT-GPCR004 CHO-K1 cell line bright-field and fluorescence microscopy and corresponding segmentation ground truth
Plain Text - 5.7 KB -
MD5: c8ed474cb7a894a97dda3ed9c0731318
README |
