'Image parameters' diaporamas de présentation

Juan M. Banda

Framework for creating large-scale content-based image retrieval (CBIR) system for solar data analysis. Juan M. Banda. Agenda. Project Objectives Datasets Framework Description Feature Extraction Attribute Evaluation Dimensionality Reduction Dissimilarity Measures Component

907 views • 76 slides

Gamma/Hadron separation in atmospheric Cherenkov telescopes Overview

Gamma/Hadron separation in atmospheric Cherenkov telescopes Overview multi-wavelength astrophysics imaging Cherenkov telescopes (IACT-s) image classification methods under study trying for a rigorous comparison. Wavelength regimes in astrophysics.

528 views • 33 slides

Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images.

Learning the Appearance of Faces: A Unifying Approach for the Analysis and Synthesis of Images. Thomas Vetter. University of Freiburg. Germany. http://graphics.informatik.uni-freiburg.de. Computer Vision & Computer Graphics.

232 views • 23 slides

Learning Specific-Class Segmentation from Diverse Data

Learning Specific-Class Segmentation from Diverse Data. M. Pawan Kuma r, Haitherm Turki , Dan Preston and Daphne Koller at ICCV 2011. VGG reading group, 29 Nov 2011, presented by Varun Gulshan. Semantic image segmentation. Main idea.

267 views • 13 slides

Defining the Business Model

223 views • 7 slides

CALLISTO (signal extraction & calibration)

MAGIC-I. MAGIC-II. Signal data. Background data. Monte Carlo data. Signal data. Background data. Monte Carlo data. CALLISTO (signal extraction & calibration). CALLISTO (signal extraction & calibration). Calibration data. Calibration data. STAR (image cleaning & Hillas par.).

88 views • 1 slides