61 to 70 of 126 Results
Feb 10, 2022 - Multispektraalfotograafia (MSI) materjalikatsetused
Vesi, Aare, 2022, "Test 18: MSI capture of Missale – TÜR, F. 7, s. 33", https://doi.org/10.23673/RE-311, DATADOI, V1
MSI capture of Missale – TÜR, F. 7, s. 33, fragment. (f. 1) Sabb. sancto; (f. 2) Fer. IV–V infra Oct. Paschae. Matricula seu catalogus illorum, qui in Academia Dorpatensi cornua deposuerunt, 1632-1665. |
Jan 24, 2022 - Arvutiteaduse andmed
Ali, Mohammed A. S.; Hollo, Kaspar; Laasfeld, Tõnis; Torp, Jane; Tahk, Maris-Johanna; Rinken, Ago; Palo, Kaupo; Parts, Leopold; Fishman, Dmytro, 2022, "ArtSeg-CHO-M4R: artifact segmentation in microscopy of ligand binding to M4 muscarinic receptor in live CHO-K1-hM4 cells.", https://doi.org/10.23673/RE-307, DATADOI, V1
The "ArtSeg-CHO-M4R, artifact segmentation in microscopy of ligand binding to M4 muscarinic receptor in live CHO-K1-hM4 cells" dataset contains microscopy images along with the ground truth binary masks for artifact segmentation from brightfield images. The dataset consists of three main directories for train, validation, and test splits. The image... |
Jan 19, 2022 - Keemia instituudi andmed
Tahk, Maris-Johanna; Torp, Jane; Ali, Mohammed A.S.; Fishman, Dmytro; Parts, Leopold; Grätz, Lukas; Müller, Christoph; Keller, Max; Veikšina, Santa; Laasfeld, Tõnis; Rinken, Ago, 2022, "UT-GPCR001 microscopy of ligand binding to M4 muscarinic receptor in live CHO-K1-hM4 cells", https://doi.org/10.23673/RE-306, DATADOI, V1
The "UT-GPCR001 microscopy of ligand binding to M4 muscarinic receptor in live CHO-K1-hM4 cells" dataset contains the raw microscopy images of the experiments along with images processed using the random forest algorithm and U-Net3 based deep convolutional neural networks for cell segmentation from bright-field images. The dataset contains experime... |
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-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images", https://doi.org/10.23673/RE-304, DATADOI, V1
The "UT-GPCR002 Machine learning models for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images" dataset contains the machine learning model files for CHO-K1 cell segmentation from fluorescence and bright-field microscopy images. Random forest-based models are implemented as Ilastik projects while deep-learning models are... |
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 14, 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-GPCR003 Fluorescence anisotropy and microscopy measurements experimental metadata of ligand binding to M4 muscarinic receptors", https://doi.org/10.23673/RE-303, DATADOI, V1
The "UT-GPCR003 Fluorescence anisotropy and microscopy measurements experimental metadata of ligand binding to M4 muscarinic receptors" dataset contains the raw fluorescence anisotropy data for ligand binding to M4 muscarinic receptors on budded baculovirus surface as well as processed data for fluorescence anisotropy measurements and microscopy me... |
Dec 8, 2021 - Ühiskonnateaduste andmed
Janar, Pekarev, 2021, "The areas of concern of systematic literature review", https://doi.org/10.23673/RE-301, DATADOI, V1
The Weaponization of artificial intelligence (AI) is upending traditional warfare as the development of autonomous weapons systems (AWS) increases in pace and sophistication. As a result, the concept of the weaponized AI, where a weapon system that, once activated, can select and engage targets without human intervention, creates serious complicati... |
Dec 5, 2021 - Füüsika andmed
Trofimov, Heido; Toll, Velle, 2021, "Pollution track days", https://doi.org/10.23673/RE-299, DATADOI, V1
Dates of polluted cloud tracks identified in MODIS satellite data. |
Sep 13, 2021 - Eesti ja üldkeeleteaduse andmed
Lippus, Pärtel; Aare, Kätlin; Malmi, Anton; Tuisk, Tuuli; Teras, Pire, 2021, "Phonetic Corpus of Estonian Spontaneous Speech v1.2", https://doi.org/10.23673/RE-293, DATADOI, V1
The Phonetic Corpus of Estonian Spontaneous Speech consists of recordings that have been annotated on different linguistic tiers including words and segments and their boundaries in the speech signal. The corpus mainly contains dialogues. The corpus can be used for studying different phonetic and linguistic research questions and for training vario... |
May 17, 2021 - Füüsika andmed
Rahu, Jorma; Toll, Velle, 2021, "Anthropogenic aerosol impacts on clouds from SEVIRI satellite data", https://doi.org/10.23673/RE-283, DATADOI, V1
Anthropogenic aerosols offset an unknown fraction of greenhouse gas warming. We use geostationary satellite data to analyse continental polluted cloud tracks originating from isolated heavy industrial pollution sources in the European part of Russia. We study the temporal evolution of the cloud water response to aerosols. This item includes the dat... |
