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  "author": "Max Coenen",
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  "author": "Max Coenen",
            
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  "author_email": "m.coenen@baustoff.uni-hannover.de",
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  "author_email": "m.coenen@baustoff.uni-hannover.de",
            
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
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  "creator_user_id": "17755db4-395a-4b3b-ac09-e8e3484ca700",
            
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  "doi": "10.25835/0027789",
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  "doi": "10.25835/0027789",
            
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  "doi_date_published": "2021-04-15",
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  "doi_date_published": "2021-04-15",
            
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  "doi_publisher": "LUIS",
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  "doi_publisher": "LUIS",
            
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  "doi_status": "true",
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  "doi_status": "true",
            
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  "domain": "https://data.uni-hannover.de",
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  "domain": "https://data.uni-hannover.de",
            
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  "groups": [],
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  "groups": [],
            
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  "have_copyright": "Yes",
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  "have_copyright": "Yes",
            
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  "id": "afd56c85-b885-4731-af17-258838c6d728",
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  "id": "afd56c85-b885-4731-af17-258838c6d728",
            
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  "license_id": "CC-BY-NC-3.0",
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  "license_id": "CC-BY-NC-3.0",
            
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  "license_title": "CC-BY-NC-3.0",
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  "license_title": "CC-BY-NC-3.0",
            
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  "maintainer": "Max Coenen",
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  "maintainer": "Max Coenen",
            
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  "maintainer_email": "m.coenen@baustoff.uni-hannover.de",
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  "maintainer_email": "m.coenen@baustoff.uni-hannover.de",
            
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  "metadata_created": "2021-10-14T10:15:54.978698",
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  "metadata_created": "2021-10-14T10:15:54.978698",
            
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  "metadata_modified": "2023-08-04T08:46:23.662308",
            
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  "name": "luh-concrete-aggregate-benchmark",
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  "name": "luh-concrete-aggregate-benchmark",
            
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  "notes": "The **Concrete Aggregate Dataset** consists of high 
21
  "notes": "The **Concrete Aggregate Dataset** consists of high 
            
22
resolution images acquired from 40 different concrete cylinders, cut 
22
resolution images acquired from 40 different concrete cylinders, cut 
            
23
lengthwise as to display the particle distribution in the concrete, 
23
lengthwise as to display the particle distribution in the concrete, 
            
24
with a ground sampling distance of 0.03mm. \r\nIn order to train and 
24
with a ground sampling distance of 0.03mm. \r\nIn order to train and 
            
25
evaluate approaches for the semantic segmentation of the concrete 
25
evaluate approaches for the semantic segmentation of the concrete 
            
26
aggregate images, currently 17 of the 40 images have been annotated by 
26
aggregate images, currently 17 of the 40 images have been annotated by 
            
27
manually associating one of the classes _aggregate_ or _suspension_ to 
27
manually associating one of the classes _aggregate_ or _suspension_ to 
            
28
each pixel. \r\nWe encourage to use the remaining unlabelled images 
28
each pixel. \r\nWe encourage to use the remaining unlabelled images 
            
29
for semi-supervised segmentation approaches, in which unlabelled data 
29
for semi-supervised segmentation approaches, in which unlabelled data 
            
30
is leveraged in addition to labelled training data in order to improve 
30
is leveraged in addition to labelled training data in order to improve 
            
31
the segmentation performance. \r\n\r\nIn the subsequent figure, five 
31
the segmentation performance. \r\n\r\nIn the subsequent figure, five 
            
32
examplary tiles of size 448x448 pixels and their annotated label masks 
32
examplary tiles of size 448x448 pixels and their annotated label masks 
            
33
are shown. The diversity of the appearance of both, _aggregate_ and 
33
are shown. The diversity of the appearance of both, _aggregate_ and 
            
34
_suspension_ can be noted.\r\n![Reference CAD 
34
_suspension_ can be noted.\r\n![Reference CAD 
            
35
728/resource/0a830d13-3e5e-450c-8bd3-b2052b015f58/download/dataset.png 
35
728/resource/0a830d13-3e5e-450c-8bd3-b2052b015f58/download/dataset.png 
            
36
\" \")\r\n\r\nIn the figure below, the distribution of the aggregate 
36
\" \")\r\n\r\nIn the figure below, the distribution of the aggregate 
            
37
particles in dependency on their sizes is depicted. The variation of 
37
particles in dependency on their sizes is depicted. The variation of 
            
38
the size of the particles contained in the data set ranges up to 15mm 
38
the size of the particles contained in the data set ranges up to 15mm 
            
39
of maximum particle diameter. However, the majority of particles, 
39
of maximum particle diameter. However, the majority of particles, 
            
40
namely more than 50% exhibit a maximum diameter of less then 3mm 
40
namely more than 50% exhibit a maximum diameter of less then 3mm 
            
41
(100px). As a consequence, approximately 80% of the particles possess 
41
(100px). As a consequence, approximately 80% of the particles possess 
            
42
an area of 5mm ^2 or less.It has to be noted that particles with a 
42
an area of 5mm ^2 or less.It has to be noted that particles with a 
            
43
size less then 20px are barely distinguishable from the suspension and 
43
size less then 20px are barely distinguishable from the suspension and 
            
44
are therefore not contained in the reference data.\r\n![Reference CAD 
44
are therefore not contained in the reference data.\r\n![Reference CAD 
            
45
source/b5a18dc0-7236-440a-b3b5-504bd5fb6d70/download/particlestats.png 
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source/b5a18dc0-7236-440a-b3b5-504bd5fb6d70/download/particlestats.png 
            
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\" \")\r\n\r\nIf you make use of the proposed data, please cite the 
46
\" \")\r\n\r\nIf you make use of the proposed data, please cite the 
            
47
publication listed below. \r\n## __Related Publications:__\r\n* 
47
publication listed below. \r\n## __Related Publications:__\r\n* 
            
48
__Coenen, M.; Schack, T.; Beyer, D.; Heipke, C. and Haist, M. 
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__Coenen, M.; Schack, T.; Beyer, D.; Heipke, C. and Haist, M. 
            
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(2021)__: Semi-Supervised Segmentation of Concrete Aggregate using 
49
(2021)__: Semi-Supervised Segmentation of Concrete Aggregate using 
            
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Consensus Regularisation and Prior Guidance. In: _ISPRS Annals of the 
50
Consensus Regularisation and Prior Guidance. In: _ISPRS Annals of the 
            
51
Photogrammetry, Remote Sensing and Spatial Information Sciences 
51
Photogrammetry, Remote Sensing and Spatial Information Sciences 
            
52
V-2-2021_, pp. 83\u201391, 
52
V-2-2021_, pp. 83\u201391, 
            
53
https://doi.org/10.5194/isprs-annals-V-2-2021-83-2021.\r\n",
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https://doi.org/10.5194/isprs-annals-V-2-2021-83-2021.\r\n",
            
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    "description": "Appelstra\u00dfe 9a\r\n__30167 
            
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Hannover__\r\n\r\nTel.: +49 511762-3722 \r\n\r\nFax: +49 511762-4736 
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Hannover__\r\n\r\nTel.: +49 511762-3722 \r\n\r\nFax: +49 511762-4736 
            
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\r\n\r\nE-Mail: institut@baustoff.uni-hannover.de 
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\r\n\r\nE-Mail: institut@baustoff.uni-hannover.de 
            
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\r\n\r\nhttps://www.baustoff.uni-hannover.de/\r\n",
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\r\n\r\nhttps://www.baustoff.uni-hannover.de/\r\n",
            
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of the concrete cylinders and the corresponding annotated 
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segmentations masks for the class _aggregate_.",
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      "display_name": "Sedimentation",
            
168
      "id": "80cf4f18-28c5-4e01-81f4-f826618d2150",
169
      "id": "80cf4f18-28c5-4e01-81f4-f826618d2150",
            
169
      "name": "Sedimentation",
170
      "name": "Sedimentation",
            
170
      "state": "active",
171
      "state": "active",
            
171
      "vocabulary_id": null
172
      "vocabulary_id": null
            
172
    },
173
    },
            
173
    {
174
    {
            
174
      "display_name": "Semantic Segmentation",
175
      "display_name": "Semantic Segmentation",
            
175
      "id": "809ad6af-28cd-43bd-974d-055a5c0f2973",
176
      "id": "809ad6af-28cd-43bd-974d-055a5c0f2973",
            
176
      "name": "Semantic Segmentation",
177
      "name": "Semantic Segmentation",
            
177
      "state": "active",
178
      "state": "active",
            
178
      "vocabulary_id": null
179
      "vocabulary_id": null
            
179
    }
180
    }
            
180
  ],
181
  ],
            
181
  "terms_of_usage": "Yes",
182
  "terms_of_usage": "Yes",
            
182
  "title": "Concrete Aggregate Benchmark",
183
  "title": "Concrete Aggregate Benchmark",
            
183
  "type": "vdataset",
184
  "type": "vdataset",
            
184
  "url": 
185
  "url": 
            
185
"https://data.uni-hannover.de/dataset/concrete-aggregate-benchmark",
186
"https://data.uni-hannover.de/dataset/concrete-aggregate-benchmark",
            
186
  "version": ""
187
  "version": ""
            
187
}
188
}