'Handwritten digit recognition' diaporamas de présentation

Part 4: ADVANCED SVM-based LEARNING METHODS

Part 4: ADVANCED SVM-based LEARNING METHODS . Vladimir Cherkassky University of Minnesota cherk001@umn.edu Presented at Tech Tune Ups, ECE Dept, June 1, 2011. Electrical and Computer Engineering. 1. 1. 1. OUTLINE. Motivation for non-standard approaches: high-dimensional data

655 views • 52 slides

Self-Paced Learning for Semantic Segmentation

643 views • 47 slides

Principal Component Analysis and Linear Discriminant Analysis for Feature Reduction

Principal Component Analysis and Linear Discriminant Analysis for Feature Reduction. Jieping Ye Department of Computer Science and Engineering Arizona State University http://www.public.asu.edu/~jye02. Outline of lecture. What is feature reduction? Why feature reduction?

966 views • 40 slides

Significance Test for Feature Selection on Image Recognition

Significance Test for Feature Selection on Image Recognition. Qianren Xu Mohamed Kamel Magdy M. A. Salama. Outline. Introduction Methodology Experiment Results Conclusion. Introduction. Problems on Features. Problems on Feature Selection Methods. Very large number Irrelevant Noise

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Chapter 6. Classification and Prediction

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Image Recognition has a wide variety of cool apps

92 views • 9 slides