In this contribution we combine different image processing and pattern recognition methodologies to map the probability of discovering epithermal mineral deposits in the northern part of the Coromandel peninsula, in New Zealand. The objective of this work is to propose a case-study where the substitution of structural geology GIS themes (commonly developed by humans) with products derived by image processing, computer-based, semi-automatic edge detection analyses, is carried out to reduce subjective input in the prospectivity analysis. Semi-automated lineament extraction results introduced in the mineral favourability statistical modelling can more easily reveal unexpected potentially mineralised target domains, being less subjective. We pr...
This study used robust spatial statistics to systematically examine regional-scale targeting criteri...
Machine learning (ML), a subfield of artificial intelligence (AI), includes computational methods to...
Novel mineral prospectivity modelling presented here applies knowledge-driven feature extraction to ...
In this contribution we combine different image processing and pattern recognition methodologies to ...
AbstractIn this contribution we combine different image processing and pattern recognition methodolo...
In this contribution we combine different image processing and pattern recognition methodologies to ...
© 2016 The Authors. In this contribution we combine different image processing and pattern recogniti...
Complexities of geological processes portrayed as certain feature in a map (e.g., faults) are natura...
In this contribution we report results of a mineral potential mapping study of the northern part of ...
Machine learning describes an array of computational and nested statistical methods whereby a comput...
Spurious evidence and spurious spatial associations between target mineral deposits and certain clas...
Large amounts of digital data must be analyzed and integrated to generate mineral potential maps, wh...
Mineral Prospectivity Conference, France.In this work, we present logistic-based mineral prospecti...
Abstract — Approaches to mineral potential mapping based on weights of evidence generally use binary...
The Trident project is located in the Domes region of the Central African Copper Belt and hosts a nu...
This study used robust spatial statistics to systematically examine regional-scale targeting criteri...
Machine learning (ML), a subfield of artificial intelligence (AI), includes computational methods to...
Novel mineral prospectivity modelling presented here applies knowledge-driven feature extraction to ...
In this contribution we combine different image processing and pattern recognition methodologies to ...
AbstractIn this contribution we combine different image processing and pattern recognition methodolo...
In this contribution we combine different image processing and pattern recognition methodologies to ...
© 2016 The Authors. In this contribution we combine different image processing and pattern recogniti...
Complexities of geological processes portrayed as certain feature in a map (e.g., faults) are natura...
In this contribution we report results of a mineral potential mapping study of the northern part of ...
Machine learning describes an array of computational and nested statistical methods whereby a comput...
Spurious evidence and spurious spatial associations between target mineral deposits and certain clas...
Large amounts of digital data must be analyzed and integrated to generate mineral potential maps, wh...
Mineral Prospectivity Conference, France.In this work, we present logistic-based mineral prospecti...
Abstract — Approaches to mineral potential mapping based on weights of evidence generally use binary...
The Trident project is located in the Domes region of the Central African Copper Belt and hosts a nu...
This study used robust spatial statistics to systematically examine regional-scale targeting criteri...
Machine learning (ML), a subfield of artificial intelligence (AI), includes computational methods to...
Novel mineral prospectivity modelling presented here applies knowledge-driven feature extraction to ...