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 | ||
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brickwedde_bernard-measurement_of-20200909153016448.pdf | 22.93 MB | Adobe PDF | View/Open |