Raian V. Maretto is PhD in Applied Computing (2020) and MSc in Remote Sensing (2011) by the Instituto Nacional de Pesquisas Espaciais (Brazilian National Institute for Space Research, INPE), and Bachelor's in Computer Science (2008) by the Universidade Federal de Ouro Preto (Federal University of Ouro Preto, UFOP). With the main expertise in the application of Deep Learning, Machine Learning, and Data Mining methods to the analysis of geospatial data. He worked as a consultant and research assistant at INPE, in the context of the FIP (Forest Investment Program) Cerrado and the MSA (Monitoring the Amazon through Satellite Imagery) projects, developing methods based on Deep Learning to automatically map deforested areas, agriculture and vegetation types in the Brazilian Cerrado and Amazon biomes. He has more than 10 years of experience in the development of Geographic Information Systems (GIS) and Remote Sensing image processing algorithms and software, participating on large software development teams following agile software development methods and working with languages like C++, Python, Lua, R, and Java. He also has participated in the development of the following systems: TerraLib library, TerraView, TerraME, GeoDMA, and recently the DeepGeo package. Main research interests are on Remote Sensing data analysis, integration of images from different sensors and natures, computer vision, machine learning, data mining, and pattern recognition.
I am PhD in Applied Computing (2020) and MSc in Remote Sensing (2011) by the Instituto Nacional de Pesquisas Espaciais (Brazilian National Institute for Space Research, INPE), and a Bachelor's in Computer Science (2008) by the Universidade Federal de Ouro Preto (Federal University of Ouro Preto, UFOP). With the main expertise in the application of Deep Learning, Machine Learning, and Data Mining methods to the analysis of geospatial data. He worked as a consultant and research assistant at INPE, in the context of the FIP (Forest Investment Program) Cerrado and the MSA (Monitoring the Amazon through Satellite Imagery) projects, developing methods based on Deep Learning to automatically map deforested areas, agriculture, and vegetation types in the Brazilian Cerrado and Amazon biomes. He has more than 10 years of experience in the development of Geographic Information Systems (GIS) and Remote Sensing image processing algorithms and software, participating on large software development teams following agile software development methods and working with languages like C++, Python, Lua, R, and Java. He also has participated in the development of the following systems: TerraLib library, TerraView, TerraME, GeoDMA, and recently the DeepGeo package. My main research interests are on Remote Sensing data analysis, integration of images from different sensors and natures, computer vision, machine learning, data mining, and pattern recognition.
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