Data · dataset · 2024
Advancing image modelling using level-sets : simulation, convergence, practical inference analysis
Listed in UP Research Data Repository
<p>The supporting material includes figures and tables detailing the use of level-sets within image modelling in the thesis titled 'Enhancing spatial image analysis: modelling perspectives on the usefulness of level-sets'.
Description
Specifically the use of level-sets for noise removal in images, enhancing the existing Adaptive Median Smoother technique. Level-sets are then used to represent images as graphical models.
These graphical model representation are then used to train model image of the fibrin networks of healthy and asthmatic patients to allow for inference to be drawn. Lastly, it is shown how level-sets can be used to improve a technique called D-RISE for improved explainability of deep learning models.</p>
Links
Where it is published
- DOI doi.org/10.25403/upresearchdata.25323946.v1 ↗
DOI / persistent id · from researchdata up ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from researchdata up ac za
Topics
- From keywords
- Applied statistics · Computer Science & AI · Earth & Environmental Science · Mathematics & Statistics · Social Science · Spatial statistics · Statistical data science
- Inferred from text
- Image 75% · Simulation 75%
Provenance · 1 source records, 14 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| UP Research Data Repository | oai:figshare.com:article/25323946 | 14 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata up ac za | connector:researchdata_up_ac_za@1.0.0 | |
| concepts[field].anzsrc:field:490501 | mapping · researchdata up ac za | vocabulary-mapper@1.0.0 | keywords['Applied statistics'] |
| concepts[field].anzsrc:field:490507 | mapping · researchdata up ac za | vocabulary-mapper@1.0.0 | keywords['Spatial statistics'] |
| concepts[field].anzsrc:field:490508 | mapping · researchdata up ac za | vocabulary-mapper@1.0.0 | keywords['Statistical data science'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata up ac za | connector:researchdata_up_ac_za@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata up ac za | connector:researchdata_up_ac_za@1.0.0 | |
| concepts[field].local:field:mathematics-statistics | mapping · researchdata up ac za | connector:researchdata_up_ac_za@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata up ac za | connector:researchdata_up_ac_za@1.0.0 | |
| concepts[method].local:method:simulation | enrichment · researchdata up ac za | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:image | enrichment · researchdata up ac za | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata up ac za | connector:researchdata_up_ac_za@1.0.0 | /metadata/dc/description |
| license | source · researchdata up ac za | connector:researchdata_up_ac_za@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata up ac za | connector:researchdata_up_ac_za@1.0.0 | |
| title | source · researchdata up ac za | connector:researchdata_up_ac_za@1.0.0 | /metadata/dc/title |