Item talk:Q166437

{

 "OpenAlex": {
   "display_name": "Machine Learning for Mineral Prospectivity Mapping",
   "description": "This cluster of papers focuses on the application of machine learning, remote sensing, and compositional data analysis techniques for mineral prospectivity mapping. It explores the use of advanced technologies such as ASTER and hyperspectral imaging to identify geological features, geochemical anomalies, and hydrothermal alterations associated with mineralization. The cluster also delves into the challenges and opportunities in using support vector machines, fractal modeling, and statistical analysis for predicting undiscovered mineral deposits.",
   "keywords": [
     "Machine Learning",
     "Mineral Prospectivity",
     "Remote Sensing",
     "Compositional Data Analysis",
     "Geological Mapping",
     "Hyperspectral Imaging",
     "Support Vector Machines",
     "Fractal Modeling",
     "Geochemical Anomalies",
     "Lithological Mapping"
   ],
   "ids": {
     "openalex": "https://openalex.org/T12157",
     "wikipedia": "https://en.wikipedia.org/wiki/Mineral_prospecting"
   },
   "subfield": {
     "id": "https://openalex.org/subfields/1702",
     "display_name": "Artificial Intelligence"
   },
   "field": {
     "id": "https://openalex.org/fields/17",
     "display_name": "Computer Science"
   },
   "domain": {
     "id": "https://openalex.org/domains/3",
     "display_name": "Physical Sciences"
   },
   "updated_date": "2024-08-12T06:00:12.098775",
   "created_date": "2024-01-23",
   "type": "topic",
   "oa_id": "T12157",
   "id": "https://openalex.org/T12157"
 }

}