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En el instante 11 de octubre de 2025, 1:23:09 UTC,
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Añadido recurso Improving Geomorphological Classification via Binary Image Processing a Improving Geomorphological Classification via Binary Image Processing
f | 1 | { | f | 1 | { |
2 | "author": "AC Salgado-Albiter, SI Valdez, J Paredes-Tavares", | 2 | "author": "AC Salgado-Albiter, SI Valdez, J Paredes-Tavares", | ||
3 | "author_email": null, | 3 | "author_email": null, | ||
4 | "creator_user_id": "a3da3ec9-3fd4-47a4-8d04-0a90b09614e0", | 4 | "creator_user_id": "a3da3ec9-3fd4-47a4-8d04-0a90b09614e0", | ||
5 | "extras": [ | 5 | "extras": [ | ||
6 | { | 6 | { | ||
7 | "key": "Publicaci\u00f3n", | 7 | "key": "Publicaci\u00f3n", | ||
8 | "value": "Conferencia" | 8 | "value": "Conferencia" | ||
9 | }, | 9 | }, | ||
10 | { | 10 | { | ||
11 | "key": "Tipo", | 11 | "key": "Tipo", | ||
12 | "value": "Publicaci\u00f3n" | 12 | "value": "Publicaci\u00f3n" | ||
13 | } | 13 | } | ||
14 | ], | 14 | ], | ||
15 | "groups": [ | 15 | "groups": [ | ||
16 | { | 16 | { | ||
17 | "description": "Este grupo integra las publicaciones | 17 | "description": "Este grupo integra las publicaciones | ||
18 | acad\u00e9micas derivadas de los proyectos de investigaci\u00f3n del | 18 | acad\u00e9micas derivadas de los proyectos de investigaci\u00f3n del | ||
19 | Observatorio Metropolitano CentroGeo. Incluye art\u00edculos | 19 | Observatorio Metropolitano CentroGeo. Incluye art\u00edculos | ||
20 | presentados en congresos nacionales e internacionales, manuscritos en | 20 | presentados en congresos nacionales e internacionales, manuscritos en | ||
21 | formato preprint, cap\u00edtulos de libro y trabajos publicados en | 21 | formato preprint, cap\u00edtulos de libro y trabajos publicados en | ||
22 | revistas cient\u00edficas especializadas. Estos materiales reflejan la | 22 | revistas cient\u00edficas especializadas. Estos materiales reflejan la | ||
23 | labor de investigaci\u00f3n, desarrollo metodol\u00f3gico y | 23 | labor de investigaci\u00f3n, desarrollo metodol\u00f3gico y | ||
24 | an\u00e1lisis territorial del observatorio, contribuyendo al avance | 24 | an\u00e1lisis territorial del observatorio, contribuyendo al avance | ||
25 | del conocimiento en temas urbanos, metropolitanos y geoespaciales.", | 25 | del conocimiento en temas urbanos, metropolitanos y geoespaciales.", | ||
26 | "display_name": "Publicaciones", | 26 | "display_name": "Publicaciones", | ||
27 | "id": "a15a6b77-ddf5-4594-acab-7e772938a5b0", | 27 | "id": "a15a6b77-ddf5-4594-acab-7e772938a5b0", | ||
28 | "image_display_url": "", | 28 | "image_display_url": "", | ||
29 | "name": "publicaciones", | 29 | "name": "publicaciones", | ||
30 | "title": "Publicaciones" | 30 | "title": "Publicaciones" | ||
31 | } | 31 | } | ||
32 | ], | 32 | ], | ||
33 | "id": "cc8c0711-59cc-4b8d-ab6e-ef0152659877", | 33 | "id": "cc8c0711-59cc-4b8d-ab6e-ef0152659877", | ||
34 | "isopen": false, | 34 | "isopen": false, | ||
35 | "license_id": null, | 35 | "license_id": null, | ||
36 | "license_title": null, | 36 | "license_title": null, | ||
37 | "maintainer": null, | 37 | "maintainer": null, | ||
38 | "maintainer_email": null, | 38 | "maintainer_email": null, | ||
39 | "metadata_created": "2025-10-11T01:23:08.460409", | 39 | "metadata_created": "2025-10-11T01:23:08.460409", | ||
n | 40 | "metadata_modified": "2025-10-11T01:23:08.460418", | n | 40 | "metadata_modified": "2025-10-11T01:23:09.226637", |
41 | "name": | 41 | "name": | ||
42 | orphological-classification-via-binary-image-processing-ec066cbffffa", | 42 | orphological-classification-via-binary-image-processing-ec066cbffffa", | ||
43 | "notes": "Landform classification is the basis for understanding and | 43 | "notes": "Landform classification is the basis for understanding and | ||
44 | describing the processes and evolution of landscape. This process | 44 | describing the processes and evolution of landscape. This process | ||
45 | usually requires elevation information from different sources, | 45 | usually requires elevation information from different sources, | ||
46 | expertise and time. Automatic geomorphological classification, via the | 46 | expertise and time. Automatic geomorphological classification, via the | ||
47 | geomorphons algorithm, supports expert classification by using local | 47 | geomorphons algorithm, supports expert classification by using local | ||
48 | ternary patterns for labeling landform elements, significantly | 48 | ternary patterns for labeling landform elements, significantly | ||
49 | reducing the computation time. Nevertheless, it presents issues such | 49 | reducing the computation time. Nevertheless, it presents issues such | ||
50 | as a noisy output, valleys that are not classified as continuous | 50 | as a noisy output, valleys that are not classified as continuous | ||
51 | forms, valleys that are classified as peaks at low altitude, flat | 51 | forms, valleys that are classified as peaks at low altitude, flat | ||
52 | zones inside the valley that are not classified as a part of it, and | 52 | zones inside the valley that are not classified as a part of it, and | ||
53 | other similar issues. In this proposal, we tackle the mentioned issues | 53 | other similar issues. In this proposal, we tackle the mentioned issues | ||
54 | for valley classification by binarizing the geomorphons output and | 54 | for valley classification by binarizing the geomorphons output and | ||
55 | applying it binary-image operators. The proposal's performance is | 55 | applying it binary-image operators. The proposal's performance is | ||
56 | measured by using binary classification metrics and expert-made | 56 | measured by using binary classification metrics and expert-made | ||
57 | groundtruth images. The results show that the accuracy, balanced | 57 | groundtruth images. The results show that the accuracy, balanced | ||
58 | accuracy, and F1 metrics are greater than those delivered by the | 58 | accuracy, and F1 metrics are greater than those delivered by the | ||
59 | geomorphons classifier for all the instances in the testing data.", | 59 | geomorphons classifier for all the instances in the testing data.", | ||
n | 60 | "num_resources": 0, | n | 60 | "num_resources": 1, |
61 | "num_tags": 14, | 61 | "num_tags": 14, | ||
62 | "organization": { | 62 | "organization": { | ||
63 | "approval_status": "approved", | 63 | "approval_status": "approved", | ||
64 | "created": "2022-05-19T00:10:30.480393", | 64 | "created": "2022-05-19T00:10:30.480393", | ||
65 | "description": "Observatorio Metropolitano CentroGeo", | 65 | "description": "Observatorio Metropolitano CentroGeo", | ||
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67 | "image_url": | 67 | "image_url": | ||
68 | "2022-05-19-001030.456616FullColor1280x1024LogoOnly.png", | 68 | "2022-05-19-001030.456616FullColor1280x1024LogoOnly.png", | ||
69 | "is_organization": true, | 69 | "is_organization": true, | ||
70 | "name": "observatorio-metropolitano-centrogeo", | 70 | "name": "observatorio-metropolitano-centrogeo", | ||
71 | "state": "active", | 71 | "state": "active", | ||
72 | "title": "Observatorio Metropolitano CentroGeo", | 72 | "title": "Observatorio Metropolitano CentroGeo", | ||
73 | "type": "organization" | 73 | "type": "organization" | ||
74 | }, | 74 | }, | ||
75 | "owner_org": "b3b3a79d-748a-4464-9471-732b6c74ec53", | 75 | "owner_org": "b3b3a79d-748a-4464-9471-732b6c74ec53", | ||
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83 | "created": "2025-10-11T01:23:09.265207", | ||||
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85 | "description": "Landform classification is the basis for | ||||
86 | understanding and describing the processes and evolution of landscape. | ||||
87 | This process usually requires elevation information from different | ||||
88 | sources, expertise and time. Automatic geomorphological | ||||
89 | classification, via the geomorphons algorithm, supports expert | ||||
90 | classification by using local ternary patterns for labeling landform | ||||
91 | elements, significantly reducing the computation time. Nevertheless, | ||||
92 | it presents issues such as a noisy output, valleys that are not | ||||
93 | classified as continuous forms, valleys that are classified as peaks | ||||
94 | at low altitude, flat zones inside the valley that are not classified | ||||
95 | as a part of it, and other similar issues. In this proposal, we tackle | ||||
96 | the mentioned issues for valley classification by binarizing the | ||||
97 | geomorphons output and applying it binary-image operators. The | ||||
98 | proposal's performance is measured by using binary classification | ||||
99 | metrics and expert-made groundtruth images. The results show that the | ||||
100 | accuracy, balanced accuracy, and F1 metrics are greater than those | ||||
101 | delivered by the geomorphons classifier for all the instances in the | ||||
102 | testing data.", | ||||
103 | "format": "HTML", | ||||
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110 | "name": "Improving Geomorphological Classification via Binary | ||||
111 | Image Processing", | ||||
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117 | "url": "https://doi.org/10.1109/enc56672.2022.9882949", | ||||
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119 | } | ||||
120 | ], | ||||
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81 | "tags": [ | 122 | "tags": [ | ||
82 | { | 123 | { | ||
83 | "display_name": "artificial-intelligence", | 124 | "display_name": "artificial-intelligence", | ||
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88 | }, | 129 | }, | ||
89 | { | 130 | { | ||
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95 | }, | 136 | }, | ||
96 | { | 137 | { | ||
97 | "display_name": "binary-image", | 138 | "display_name": "binary-image", | ||
98 | "id": "329690c5-40f4-4c61-ae57-2f0c92b82526", | 139 | "id": "329690c5-40f4-4c61-ae57-2f0c92b82526", | ||
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130 | }, | 171 | }, | ||
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158 | }, | 199 | }, | ||
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181 | "title": "Improving Geomorphological Classification via Binary Image | 222 | "title": "Improving Geomorphological Classification via Binary Image | ||
182 | Processing", | 223 | Processing", | ||
183 | "type": "dataset", | 224 | "type": "dataset", | ||
184 | "url": "https://doi.org/10.1109/enc56672.2022.9882949", | 225 | "url": "https://doi.org/10.1109/enc56672.2022.9882949", | ||
185 | "version": null | 226 | "version": null | ||
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