Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan
Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan
Computer Science Senior Theses
We introduce a framework that combines Gaussian Process models, robotic sensor measurements, and sampling data to predict spatial fields. In this context, a spatial field refers to the distribution of a variable throughout a specific area, such as temperature or pH variations over the surface of a lake. Whereas existing methods tend to analyze only the particular field(s) of interest, our approach optimizes predictions through the effective use of all available data. We validated our framework on several datasets, showing that errors can decline by up to two-thirds through the inclusion of additional colocated measurements. In support of adaptive sampling, …
Algorithmic Bias: Causes And Effects On Marginalized Communities, Katrina M. Baha
Algorithmic Bias: Causes And Effects On Marginalized Communities, Katrina M. Baha
Undergraduate Honors Theses
Individuals from marginalized backgrounds face different healthcare outcomes due to algorithmic bias in the technological healthcare industry. Algorithmic biases, which are the biases that arise from the set of steps used to solve or analyze a problem, are evident when people from marginalized communities use healthcare technology. For example, many pulse oximeters, which are the medical devices used to measure oxygen saturation in the blood, are not able to accurately read people who have darker skin tones. Thus, people with darker skin tones are not able to receive proper health care due to their pulse oximetry data being inaccurate. This …
Deeppatent2: A Large-Scale Benchmarking Corpus For Technical Drawing Understanding, Kehinde Ajayi, Xin Wei, Martin Gryder, Winston Shields, Jian Wu, Shawn M. Jones, Michal Kucer, Diane Oyen
Deeppatent2: A Large-Scale Benchmarking Corpus For Technical Drawing Understanding, Kehinde Ajayi, Xin Wei, Martin Gryder, Winston Shields, Jian Wu, Shawn M. Jones, Michal Kucer, Diane Oyen
Computer Science Faculty Publications
Recent advances in computer vision (CV) and natural language processing have been driven by exploiting big data on practical applications. However, these research fields are still limited by the sheer volume, versatility, and diversity of the available datasets. CV tasks, such as image captioning, which has primarily been carried out on natural images, still struggle to produce accurate and meaningful captions on sketched images often included in scientific and technical documents. The advancement of other tasks such as 3D reconstruction from 2D images requires larger datasets with multiple viewpoints. We introduce DeepPatent2, a large-scale dataset, providing more than 2.7 million …