Titlebook: Learning Discrete Mathematics with ISETL; Nancy Baxter,Ed Dubinsky,Gary Levin Book 1989 Springer-Verlag New York Inc. 1989 Combinatorics.M

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Nancy Baxter,Ed Dubinsky,Gary Levinincluding but not limited to shape analysis, action recognition, subspace clustering and motion segmentation. For these problems, the features usually lie in a very high-dimensional Grassmann manifold and hence an appropriate dimensionality reduction technique is called for in order to curtail the c

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Nancy Baxter,Ed Dubinsky,Gary Levination model from high resolution (HR) to low resolution (LR) to create paired data when training a supervised algorithm. Existing super-resolution algorithms make assumptions about the slice selection profile since it is not readily known for a given image. In this work, we estimate a slice selectio

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Nancy Baxter,Ed Dubinsky,Gary Levinogical changes. Disentangling the variability in spatiotemporal progression patterns offers major benefits for patient stratification and disease understanding but is a complex methodological challenge. Here we present Temporal Subtype and Stage Inference (T-SuStaIn), a technique that uniquely integ

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omy of pancreatic lesions, i.e., normal, seven major types of lesions, and “other” lesions, is critical to aid the clinical decision-making of patient management and treatment. However, existing work focus on segmentation and classification for very specific lesion types (PDAC) or groups. Moreover,

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