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sensors, laboratory and greenhouse space, as well as cloud and supercomputing resources. We also engage closely with researchers at University of California campuses, especially those in Davis. Learning
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collecting soil, plant, and water samples; monitoring soil moisture with advanced sensors; organizing and processing research data; and contributing to modeling efforts that examine water and nutrient dynamics
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to classify rangeland plant species, and (2) using transfer learning to adapt deep learning models for imagery analysis to varying UAV sensors and conditions. These techniques will allow you to identify and
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Implementing Bayesian networks and uncertainty quantification techniques to account for sensor noise and model confidence limits Designing, training, and fine-tuning computer vision models to extract clinically
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variety of meteorological and snowpack sensors. Learn to document avalanche activity and environmental conditions using standardized protocols. Data Analysis and Modeling Train to process and analyze
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semiconductor-free emerging sensing materials (plasmonic metal metasurfaces). You will consider how this might represent the first steps to a new generation of inexpensive and uncooled sensors, whether