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Super-Resolution Through Neighbor Embedding

Super-Resolution Through Neighbor Embedding

Super-Resolution Through Neighbor Embedding. Hong Chang, Dit-Yan Yeung and Yimin Xiong. Presented By: Ashish Parulekar, Ritendra Datta, Shiva Kasiviswanathan and Siddharth Pal. Contents. Introduction What is Super resolution ? Multiframe superresolution.

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1.44k views • 47 slides
Dimensionality Reduction

Dimensionality Reduction

Dimensionality Reduction. CS 685: Special Topics in Data Mining Jinze Liu. Overview. What is Dimensionality Reduction? Simplifying complex data Using dimensionality reduction as a Data Mining “tool” Useful for both “data modeling” and “data analysis” Tool for “clustering” and “regression”

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714 views • 46 slides
Computer examples

Computer examples

Computer examples. Tenenbaum, de Silva, Langford “A Global Geometric Framework for Nonlinear Dimensionality Reduction”. Statue face database. 698 64x64 grayscale images 2 mins, 12 secs on a ~600 (?) MHz PIII. The computed manifold. The computed manifold.

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640 views • 37 slides
Clustering Linear and Nonlinear Manifolds using Generalized Principal Components Analysis

Clustering Linear and Nonlinear Manifolds using Generalized Principal Components Analysis

Clustering Linear and Nonlinear Manifolds using Generalized Principal Components Analysis. René Vidal Center for Imaging Science Institute for Computational Medicine Johns Hopkins University. Data segmentation and clustering. Given a set of points, separate them into multiple groups

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400 views • 37 slides
Manifold learning: MDS and Isomap

Manifold learning: MDS and Isomap

Manifold learning: MDS and Isomap. Manifold learning. A manifold is a topological space which is locally Euclidean. Manifold learning. A global geometric framework for nonlinear dimensionality reduction Tenenbaum JB, de Silva V., and Langford JC Science, 290: 2319–2323, 2000

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844 views • 28 slides
Video Analysis via Nonlinear Dimensionality Reduction Technique

Video Analysis via Nonlinear Dimensionality Reduction Technique

Video Analysis via Nonlinear Dimensionality Reduction Technique. Yi Li Colin Zheng. Roadmap. Nonlinear Dimensionality Reduction LLE Isomap Video Analysis A trajectory thorough an image space Low dimension embedding. Problem Setting. Input

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177 views • 14 slides

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