Please use this identifier to cite or link to this item:
http://doi.org/10.25358/openscience-5122| Authors: | Brickwedde, Bernard |
| Title: | Measurement of the differential Drell-Yan production cross-section and application of deep convolutional neural networks on event images in the context of pileup mitigation |
| Online publication date: | 10-Sep-2020 |
| Year of first publication: | 2020 |
| Language: | english |
| DDC: | 500 Naturwissenschaften 500 Natural sciences and mathematics 530 Physik 530 Physics |
| Institution: | Johannes Gutenberg-Universität Mainz |
| Department: | FB 08 Physik, Mathematik u. Informatik |
| Place: | Mainz |
| ROR: | https://ror.org/023b0x485 |
| DOI: | http://doi.org/10.25358/openscience-5122 |
| URN: | urn:nbn:de:hebis:77-openscience-457f07ef-20c4-406b-b1ce-bed889b56a082 |
| Version: | Original work |
| Publication type: | Dissertation |
| License: | CC BY-NC-ND |
| Information on rights of use: | http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Extent: | v, 199 Seiten |
| Appears in collections: | JGU-Publikationen |
Files in This Item:
| File | Description | Size | Format | ||
|---|---|---|---|---|---|
 | brickwedde_bernard-measurement_of-20200909153016448.pdf | 22.93 MB | Adobe PDF | View/Open |