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Visar resultat 1 - 5 av 14 uppsatser som matchar ovanstående sökkriterier.
1. Land cover classification using machine-learning techniques applied to fused multi-modal satellite imagery and time series data
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : Land cover classification is one of the most studied topics in the field of remote sensing, involving the use of data from satellite sensors to analyze and categorize different land surface types. There are numerous satellite products available, each offering different spatial, spectral, and temporal resolutions. LÄS MER
2. Predicting Health and Living Standards of India using Deep Learning
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Poverty eradication is an inexorable process in human growth [21], with poverty estimation being the first and most important stage. Identifying strategies for poverty reduction programs and distributing resources appropriately requires determining the poverty levels of distinct places throughout the world. LÄS MER
3. Development of a Level-0 Geoprocessing Platform for a Multispectral Remote Sensing Payload
Master-uppsats, KTH/Lättkonstruktioner, marina system, flyg- och rymdteknik, rörelsemekanikSammanfattning : This thesis presented an overview of the development of a geolocating algorithm as part of a geoprocessor for raw satellite imagery. This algorithm was devised for and limited by the specifications of a state-of-the-art multispectral telescope designed by Aistech Space, hosted onboard the Guardian spacecraft, which will observe Earth through the visible, near infrared, and thermal infrared bands of the electromagnetic spectrum. LÄS MER
4. Exploring Diversity of Spectral Data in Cloud Detection with Machine Learning Methods : Contribution of Near Infrared band in improving cloud detection in winter images
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Cloud detection on satellite imagery is an essential pre-processing step for several remote sensing applications. In general, machine learning based methods for cloud detection perform well, especially the ones based on deep learning as they consider both spatial and spectral features of the input image. LÄS MER
5. Estimation of Water Depth from Multispectral Drone Imagery : A suitability assessment of CNN models for bathymetry retrieval in shallow water areas
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Aedes aegypti and Aedes albopictus are the main vector species for dengue disease and zika, two arboviruses that affect a substantial fraction of the global population. These mosquitoes breed in very slow-moving or standing pools of water, so detecting and managing these potential breeding habitats is a crucial step in preventing the spread of these diseases. LÄS MER