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Full-Text Articles in Computational Engineering
Evaluating Machine Learning Models For Semantic Segmentation Over Cloud Images For Classification, Harsh Nagarkar
Evaluating Machine Learning Models For Semantic Segmentation Over Cloud Images For Classification, Harsh Nagarkar
Honors Theses
Due to the increasing number of available approaches nowadays, choosing the most accurate image semantic segmentation model has become hard. The purpose of this research is to find the best-performing image semantic segmentation model for Cloud classification. For the purpose of this study, a data set of cloud images from the Max Planck Institute for meteorology is used. These images were taken from the by two NASA space satellite.Three main models UNet, PSPNet and FPN were used in combination of 4 differ-ent encoder Inception-ResNet-v2, MobileNet-v2, ResNet-34, and ResNet 101. After training all the models in the Mississippi Center for Super …
Minet Magnetic Indoor Localization, Michael Drake
Minet Magnetic Indoor Localization, Michael Drake
Honors Theses
Indoor localization is a modern problem of computer science that has no unified solution, as there are significant trade-offs involved with every technique. Magnetic localization, though less popular than WiFi signal based localization, is a sub-field that is rooted in infrastructure-free design, which can allow universal setup. Magnetic localization is also often paired with probabilistic programming, which provides a powerful method of estimation, given a limited understanding of the environment. This thesis presents Minet, which is a particle filter based localization system using the Earth's geomagnetic field. It explores the novel idea of state space limitation as a method of …