'Vector quantization' diaporamas de présentation

Recap

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Unsupervised Learning of Visual Object Categories

Unsupervised Learning of Visual Object Categories. Michael Pfeiffer pfeiffer@igi.tugraz.at. References. M. Weber 1 , M. Welling 1 , P. Perona 1 (2000) Unsupervised Learning of Models for Recognition Li Fei-Fei 1 , R. Fergus 2 , P. Perona 1 (2003)

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Voice Activated Un-Lock Technology

Voice Activated Un-Lock Technology. V.A.U.L.T A Matlab based Simulation. By. Siddharth Advani B2213401 Anand Gokhale B2213420 Vishal Jain B2213426 Guided by Dr. P.M. Patil. OBJECTIVE.

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BIRCH: A New Data Clustering Algorithm and Its Applications

BIRCH: A New Data Clustering Algorithm and Its Applications. Tian Zhang, Raghu Ramakrishnan, Miron Livny Presented by Qiang Jing On CS 331, Spring 2006. Problem Introduction. Data clustering How do we divide n data points into k groups?

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Lossy Compression Algorithms

Lossy Compression Algorithms. Chapter 8. outline. 8.1 Introduction 8.2 Distortion Measures 8.3 The Rate-Distortion Theory 8.4 Quantization 8.5 Transform Coding 8.6 Wavelet-Based Coding 8.7 Wavelet Packets 8.8 Embedded Zerotree of Wavelet Coefficients

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ECE 4371, Fall, 2009

ECE 4371, Fall, 2009. Zhu Han Department of Electrical and Computer Engineering Class 10 Sep. 24 th , 2009. 0111. 0110. 0100. 0101. Resolution= 1 part in 2 n. 0011. 0010. 0001. 0000. 1111. 1110. 1100. 1010. 1101. 1011. 1001. PCM. 0000. 0110. 0111. 0011. 1100. 1001.

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Unsupervised learning (II)

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Data Compression for Hardware-accelerated Volume Rendering

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V. Megalooikonomou Data Compression

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Lossless index coding for indexed colour images

Lossless index coding for indexed colour images. Author: Y-C Hu, C-Y Chiang, W-L Chen and W-K Chou Source: Imaging Science Journal, Vol. 60,No.1,pp.54-63,2012 Speaker: Meng -Jing Tsai Date: 2012.03.06. Outline. Introductions Colour image quantization (CIQ)

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Dynamical analysis of LVQ type learning rules

Dynamical analysis of LVQ type learning rules. Barbara Hammer. Michael Biehl, Anarta Ghosh. Clausthal University of Technology Institute of Computing Science. Rijksuniversiteit Groningen Mathematics and Computing Science http://www.cs.rug.nl/~biehl m.biehl@rug.nl.

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Nonlinear Unsupervised Feature Learning How Local Similarities Lead to Global Coding

Nonlinear Unsupervised Feature Learning How Local Similarities Lead to Global Coding. Amirreza Shaban. Outline. Feature Learning Coding methods Vector Quantization Sparse Coding Local Coordinate Coding Locality-constrained Linear Coding Local Similarity Global Coding

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Locality-constrained Linear Coding for Image Classification

Locality-constrained Linear Coding for Image Classification. Presenter : Han-Mu Park. Locality-constrained Linear Coding for Image Classification, CVPR 2010. Contents. Introduction Coding methods Proposed method Experimental results Conclusion References.

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Vector Quantization

Vector Quantization. outline. Introduction Two measurement : quality of image and bit rate Advantages of Vector Quantization over Scalar Quantization The Linde-Buzo-Gray Algotithm Cell-split algorithm Standard VQ encoding Summary. Two measurement. Quality of image.

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Artificial Neural Networks

Artificial Neural Networks . R. Michael Winters Music Information Retrieval Dr. Ichiro Fujinaga February 28, 2012. Outline. A brief history of ANN Quick facts about biological n eural networks Simple explanation of mathematical implementation Detailed mathematical implementation

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Local and global mappings of topology representing networks

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Stable Biometric Features

Stable Biometric Features. Description (not definition): Biometric features whose value change very infrequently among multiple prints of a finger

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NITFS Compliance Registration

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Optimized entropy-constrained vector quantization of lossy vector map compression

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