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CS448f: Image Processing For Photography and Vision

CS448f: Image Processing For Photography and Vision

CS448f: Image Processing For Photography and Vision. Alignment. Assignment 1 Grading. Graded out of 20 4 points for correctness 4 points for readability 8 points for accuracy 4 for hitting the minimum (0.07) 7 for hitting the goal (0.05) Linear in between 4 points for speed

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807 views • 74 slides
Gatzen, Groenemeijer: Forecasting tornadoes using model- and sounding derived parameters

Gatzen, Groenemeijer: Forecasting tornadoes using model- and sounding derived parameters

Gatzen, Groenemeijer: Forecasting tornadoes using model- and sounding derived parameters. Introduction A: Importance of sounding information doing convective forecasts. http://physics.uwstout.edu/wx/Notes/. Introduction B: Sounding-derived parameters using parcel-theory. Introduction B:

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789 views • 60 slides
Extracting Regional Knowledge from Spatial Datasets

Extracting Regional Knowledge from Spatial Datasets

Extracting Regional Knowledge from Spatial Datasets. Christoph F. Eick Department of Computer Science, University of Houston Motivation: Why is Regional Knowledge Important? Region Discovery Framework A Family of Clustering Algorithms for Region Discovery

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779 views • 55 slides
The Architecture of Linkage Disequilibrium Blocks Across Chromosomes 6, 21, & 22

The Architecture of Linkage Disequilibrium Blocks Across Chromosomes 6, 21, & 22

The Architecture of Linkage Disequilibrium Blocks Across Chromosomes 6, 21, & 22. Linkage Disequilibirum Mapping. Linkage disequilibrium mapping is based on the allelic association between a SNP surrogate marker and the phenotype influencing mutation being sought

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595 views • 39 slides
Discovering Interesting Regions in Spatial Data Sets using Supervised Clustering

Discovering Interesting Regions in Spatial Data Sets using Supervised Clustering

Discovering Interesting Regions in Spatial Data Sets using Supervised Clustering. Christoph F. Eick, Banafsheh Vaezian, Dan Jiang, Jing Wang PKDD Conference, Berlin, Sept. 21, 2006 Department of Computer Science University of Houston, Texas, USA Organization

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397 views • 28 slides
Discovery of Interesting Spatial Regions

Discovery of Interesting Spatial Regions

Discovery of Interesting Spatial Regions. Objectives : Applying supervised clustering algorithms for discovery of interesting regions in spatial datasets Example : Finding regions with very high or very low levels of poverty in the state of Wyoming using census data. Algorithms

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158 views • 1 slides

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