Personal Information
Organização/Local de trabalho
Manzini, Manzini Swaziland
Cargo
Geospatial Data Scientist, Environmental Scientist
Setor
Education
Sobre
Dr. Dlamini is an environmental and geospatial data scientist. He also lectures on Ecology, Applied Biology, Remote Sensing and GIS at the University of Swaziland. His experience spans a wide variety of scientific and management areas such as environmental science, environmental law, ecology, remote sensing, and geographic information systems. He also has experience in consulting, lecturing and research in the same fields. His research passions are in artificial intelligence and machine learning applications, particularly Bayesian networks in applied remote sensing, geospatial and ecological modeling and biodiversity-climate interactions. He has also published various articles in peer-rev...
Marcadores
invasive species
bayesian network
environment
remote sensing
forest fire
gis
earth observation
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Apresentações
(2)Gostaram
(2)Bayesian network-based predictive analytics applied to invasive species distribution
Wisdom Dlamini
•
Há 8 anos
Theories and Applications of Spatial-Temporal Data Mining and Knowledge Discovery
Beniamino Murgante
•
Há 12 anos
Personal Information
Organização/Local de trabalho
Manzini, Manzini Swaziland
Cargo
Geospatial Data Scientist, Environmental Scientist
Setor
Education
Sobre
Dr. Dlamini is an environmental and geospatial data scientist. He also lectures on Ecology, Applied Biology, Remote Sensing and GIS at the University of Swaziland. His experience spans a wide variety of scientific and management areas such as environmental science, environmental law, ecology, remote sensing, and geographic information systems. He also has experience in consulting, lecturing and research in the same fields. His research passions are in artificial intelligence and machine learning applications, particularly Bayesian networks in applied remote sensing, geospatial and ecological modeling and biodiversity-climate interactions. He has also published various articles in peer-rev...
Marcadores
invasive species
bayesian network
environment
remote sensing
forest fire
gis
earth observation
Ver mais