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f | 1 | { | f | 1 | { |
2 | "author": "Dreisbach, Maximilian", | 2 | "author": "Dreisbach, Maximilian", | ||
3 | "author_email": "", | 3 | "author_email": "", | ||
4 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | 4 | "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700", | ||
5 | "doi": "10.35097/1333", | 5 | "doi": "10.35097/1333", | ||
6 | "doi_date_published": "2023", | 6 | "doi_date_published": "2023", | ||
7 | "doi_publisher": "", | 7 | "doi_publisher": "", | ||
8 | "doi_status": "True", | 8 | "doi_status": "True", | ||
9 | "extra_authors": [ | 9 | "extra_authors": [ | ||
10 | { | 10 | { | ||
11 | "extra_author": "Leister, Robin", | 11 | "extra_author": "Leister, Robin", | ||
12 | "orcid": "0000-0002-0286-8183" | 12 | "orcid": "0000-0002-0286-8183" | ||
13 | }, | 13 | }, | ||
14 | { | 14 | { | ||
15 | "extra_author": "Probst, Matthias", | 15 | "extra_author": "Probst, Matthias", | ||
16 | "orcid": "0000-0001-8729-0482" | 16 | "orcid": "0000-0001-8729-0482" | ||
17 | }, | 17 | }, | ||
18 | { | 18 | { | ||
19 | "extra_author": "Friederich, Pascal", | 19 | "extra_author": "Friederich, Pascal", | ||
20 | "orcid": "0000-0003-4465-1465" | 20 | "orcid": "0000-0003-4465-1465" | ||
21 | }, | 21 | }, | ||
22 | { | 22 | { | ||
23 | "extra_author": "Stroh, Alexander", | 23 | "extra_author": "Stroh, Alexander", | ||
24 | "orcid": "" | 24 | "orcid": "" | ||
25 | }, | 25 | }, | ||
26 | { | 26 | { | ||
27 | "extra_author": "Kriegseis, Jochen", | 27 | "extra_author": "Kriegseis, Jochen", | ||
28 | "orcid": "0000-0002-2737-2539" | 28 | "orcid": "0000-0002-2737-2539" | ||
29 | } | 29 | } | ||
30 | ], | 30 | ], | ||
31 | "groups": [], | 31 | "groups": [], | ||
32 | "id": "d4d97ad0-74f0-429b-91c4-789d5203d399", | 32 | "id": "d4d97ad0-74f0-429b-91c4-789d5203d399", | ||
33 | "isopen": false, | 33 | "isopen": false, | ||
34 | "license_id": "CC BY 4.0 Attribution", | 34 | "license_id": "CC BY 4.0 Attribution", | ||
35 | "license_title": "CC BY 4.0 Attribution", | 35 | "license_title": "CC BY 4.0 Attribution", | ||
36 | "metadata_created": "2023-08-04T08:50:33.725300", | 36 | "metadata_created": "2023-08-04T08:50:33.725300", | ||
t | 37 | "metadata_modified": "2023-08-04T09:04:11.678275", | t | 37 | "metadata_modified": "2023-08-04T09:29:05.241864", |
38 | "name": "rdr-doi-10-35097-1333", | 38 | "name": "rdr-doi-10-35097-1333", | ||
39 | "notes": "TechnicalRemarks: This repository contains the | 39 | "notes": "TechnicalRemarks: This repository contains the | ||
40 | supplementary data to our contribution \"Particle Detection by means | 40 | supplementary data to our contribution \"Particle Detection by means | ||
41 | of Neural Networks and Synthetic Training Data Refinement in | 41 | of Neural Networks and Synthetic Training Data Refinement in | ||
42 | Defocusing Particle Tracking Velocimetry\" to the 2022 Measurement | 42 | Defocusing Particle Tracking Velocimetry\" to the 2022 Measurement | ||
43 | Science and Technology special issue on the topic \u201cMachine | 43 | Science and Technology special issue on the topic \u201cMachine | ||
44 | Learning and Data Assimilation techniques for fluid flow | 44 | Learning and Data Assimilation techniques for fluid flow | ||
45 | measurements\u201d.\r\nThis data includes annotated images used for | 45 | measurements\u201d.\r\nThis data includes annotated images used for | ||
46 | the training of neural networks for particle detection on DPTV | 46 | the training of neural networks for particle detection on DPTV | ||
47 | recordings as well as unannotated particle images used for training of | 47 | recordings as well as unannotated particle images used for training of | ||
48 | the image-to-image translation networks for the generation of refined | 48 | the image-to-image translation networks for the generation of refined | ||
49 | synthetic training data, as presented in the manuscript.\r\nThe neural | 49 | synthetic training data, as presented in the manuscript.\r\nThe neural | ||
50 | networks for particle detection trained on the aforementioned data are | 50 | networks for particle detection trained on the aforementioned data are | ||
51 | contained in this repository as well.\r\n\r\nAn explanation on the use | 51 | contained in this repository as well.\r\n\r\nAn explanation on the use | ||
52 | of this data and the trained neural networks, containing an example | 52 | of this data and the trained neural networks, containing an example | ||
53 | script can be found on GitHub | 53 | script can be found on GitHub | ||
54 | (https://github.com/MaxDreisbach/DPTV_ML_Particle_detection)", | 54 | (https://github.com/MaxDreisbach/DPTV_ML_Particle_detection)", | ||
55 | "num_resources": 0, | 55 | "num_resources": 0, | ||
56 | "num_tags": 3, | 56 | "num_tags": 3, | ||
57 | "orcid": "0000-0001-6308-0982", | 57 | "orcid": "0000-0001-6308-0982", | ||
58 | "organization": { | 58 | "organization": { | ||
59 | "approval_status": "approved", | 59 | "approval_status": "approved", | ||
60 | "created": "2023-01-12T13:30:23.238233", | 60 | "created": "2023-01-12T13:30:23.238233", | ||
61 | "description": "RADAR (Research Data Repository) is a | 61 | "description": "RADAR (Research Data Repository) is a | ||
62 | cross-disciplinary repository for archiving and publishing research | 62 | cross-disciplinary repository for archiving and publishing research | ||
63 | data from completed scientific studies and projects. The focus is on | 63 | data from completed scientific studies and projects. The focus is on | ||
64 | research data from subjects that do not yet have their own | 64 | research data from subjects that do not yet have their own | ||
65 | discipline-specific infrastructures for research data management. ", | 65 | discipline-specific infrastructures for research data management. ", | ||
66 | "id": "013c89a9-383c-4200-8baa-0f78bf1d91f9", | 66 | "id": "013c89a9-383c-4200-8baa-0f78bf1d91f9", | ||
67 | "image_url": "radar-logo.svg", | 67 | "image_url": "radar-logo.svg", | ||
68 | "is_organization": true, | 68 | "is_organization": true, | ||
69 | "name": "radar", | 69 | "name": "radar", | ||
70 | "state": "active", | 70 | "state": "active", | ||
71 | "title": "RADAR", | 71 | "title": "RADAR", | ||
72 | "type": "organization" | 72 | "type": "organization" | ||
73 | }, | 73 | }, | ||
74 | "owner_org": "013c89a9-383c-4200-8baa-0f78bf1d91f9", | 74 | "owner_org": "013c89a9-383c-4200-8baa-0f78bf1d91f9", | ||
75 | "private": false, | 75 | "private": false, | ||
76 | "production_year": "2022", | 76 | "production_year": "2022", | ||
77 | "publication_year": "2023", | 77 | "publication_year": "2023", | ||
78 | "publishers": [ | 78 | "publishers": [ | ||
79 | { | 79 | { | ||
80 | "publisher": "Karlsruhe Institute of Technology" | 80 | "publisher": "Karlsruhe Institute of Technology" | ||
81 | } | 81 | } | ||
82 | ], | 82 | ], | ||
83 | "relationships_as_object": [], | 83 | "relationships_as_object": [], | ||
84 | "relationships_as_subject": [], | 84 | "relationships_as_subject": [], | ||
85 | "repository_name": "RADAR (Research Data Repository)", | 85 | "repository_name": "RADAR (Research Data Repository)", | ||
86 | "resources": [], | 86 | "resources": [], | ||
87 | "services_used_list": "", | 87 | "services_used_list": "", | ||
88 | "source_metadata_created": "2023", | 88 | "source_metadata_created": "2023", | ||
89 | "source_metadata_modified": "", | 89 | "source_metadata_modified": "", | ||
90 | "state": "active", | 90 | "state": "active", | ||
91 | "subject_areas": [ | 91 | "subject_areas": [ | ||
92 | { | 92 | { | ||
93 | "subject_area_additional": "", | 93 | "subject_area_additional": "", | ||
94 | "subject_area_name": "Engineering" | 94 | "subject_area_name": "Engineering" | ||
95 | } | 95 | } | ||
96 | ], | 96 | ], | ||
97 | "tags": [ | 97 | "tags": [ | ||
98 | { | 98 | { | ||
99 | "display_name": "Defocusing Particle Tracking Velocimetry", | 99 | "display_name": "Defocusing Particle Tracking Velocimetry", | ||
100 | "id": "f040c870-1607-4786-ad68-5b1467fb4435", | 100 | "id": "f040c870-1607-4786-ad68-5b1467fb4435", | ||
101 | "name": "Defocusing Particle Tracking Velocimetry", | 101 | "name": "Defocusing Particle Tracking Velocimetry", | ||
102 | "state": "active", | 102 | "state": "active", | ||
103 | "vocabulary_id": null | 103 | "vocabulary_id": null | ||
104 | }, | 104 | }, | ||
105 | { | 105 | { | ||
106 | "display_name": "Particle Detection", | 106 | "display_name": "Particle Detection", | ||
107 | "id": "c2a2a5f8-65f1-4546-8eff-daf2bc07356d", | 107 | "id": "c2a2a5f8-65f1-4546-8eff-daf2bc07356d", | ||
108 | "name": "Particle Detection", | 108 | "name": "Particle Detection", | ||
109 | "state": "active", | 109 | "state": "active", | ||
110 | "vocabulary_id": null | 110 | "vocabulary_id": null | ||
111 | }, | 111 | }, | ||
112 | { | 112 | { | ||
113 | "display_name": "Synthetic Training Data Refinement", | 113 | "display_name": "Synthetic Training Data Refinement", | ||
114 | "id": "9e71f75d-1c7d-4164-9489-6a899c11c676", | 114 | "id": "9e71f75d-1c7d-4164-9489-6a899c11c676", | ||
115 | "name": "Synthetic Training Data Refinement", | 115 | "name": "Synthetic Training Data Refinement", | ||
116 | "state": "active", | 116 | "state": "active", | ||
117 | "vocabulary_id": null | 117 | "vocabulary_id": null | ||
118 | } | 118 | } | ||
119 | ], | 119 | ], | ||
120 | "title": "Particle detection by means of neural networks and | 120 | "title": "Particle detection by means of neural networks and | ||
121 | synthetic training data refinement in defocusing particle tracking | 121 | synthetic training data refinement in defocusing particle tracking | ||
122 | velocimetry (data)", | 122 | velocimetry (data)", | ||
123 | "type": "vdataset", | 123 | "type": "vdataset", | ||
124 | "url": "https://doi.org/10.35097/1333" | 124 | "url": "https://doi.org/10.35097/1333" | ||
125 | } | 125 | } |