'Generic features' diaporamas de présentation

TRAMTRAIN: THE 2ND GENERATION

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Deep Learning

Deep Learning. Early Work Why Deep Learning Stacked Auto Encoders Deep Belief Networks. Deep Learning Overview. Train networks with many layers (vs. shallow nets with just a couple of layers) Multiple layers work to build an improved feature space

727 views • 34 slides

Deep Learning

Deep Learning. Early Work Why Deep Learning Stacked Auto Encoders Deep Belief Networks. Deep Learning Overview. Train networks with many layers (vs. shallow nets with just a couple of layers) Multiple layers work to build an improved feature space

872 views • 33 slides

Principal Component Analysis & Multidimensional scaling

Principal Component Analysis & Multidimensional scaling. Problem: Too much data!. Pat1 Pat2 Pat3 Pat4 Pat5 Pat6 Pat7 Pat8 Pat9 209619_at 7758 4705 5342 7443 8747 4933 7950 5031 5293 7546 32541_at 280 387 392 238 385 329 337 163 225 288

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With contributions of: Wayne Angevine (NOAA) Sunkanta Basu (TTU) Eric Bazile (MeteoFrance)

INTERCOMPARISON AND EVALUATION OF SINGLE-COLUMN MODELS FOR GABLS3: PRELIMINARY RESULTS Fred Bosveld, Peter Baas, Cisco de Bruijn and Bert Holtslag. With contributions of: Wayne Angevine (NOAA) Sunkanta Basu (TTU) Eric Bazile (MeteoFrance) John Edward (MetOffice) Michael Ek (NCEP

302 views • 30 slides

Convolutional Decision Trees

Convolutional Decision Trees. Dmitry Laptev, Joachim M. Buhmann Machine Learning Lab, ETH Zurich. Connectomics *. * Reconstruction and study of Connectome : a map of neuron connections. Connectomics. Hard to automate On a whole-brain scale it is simply necessary Good techniques are:

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MEP 203 CONTEMPORARY MEDIA THEORY

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OTHELLO by William Shakespeare

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Content-Based Image Retrieval (CBIR)

Content-Based Image Retrieval (CBIR). From Wikipedia: the application of computer vision to the image retrieval problem, that is, the problem of searching for digital images in large databases. "Content-based" means that the search will analyze the actual contents of the image.

295 views • 6 slides