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% Describes all steps of behavior recognition; example for facial expressions. % % The file describes the following: % 1) data format [3 choices] % 2) feature detection & description [2 choices] %

% Test the performance of behavior recognition using cross validation. % % Training occurs on all but (n-1) of the sets and testing on the remaining one, giving a % total of (n) training/testing scena

% CUBOIDS/RECOGNITION % See also % % Demo % recognition_demo - Describes all steps of behavior recognition; example for facial expressions. % datadir - Get location of data; alter

% Test the performance of behavior recognition using the cuboid representation. % % Given n sets of data, each containing multiple data instances, we train on 1 set at a % time, and then test on each

function lpr_loc() % license plate recognition - car plate location based on color model % modified by ZHAO Hui, April 30th,2005 I=imread('Car.jpg'); [y,x,z]=size(I); myI=double(I); %%%%%%%%%%%

function lpr_loc() % license plate recognition - car plate location based on color model % modified by ZHAO Hui, April 30th,2005 I=imread('Car.jpg'); [y,x,z]=size(I); myI=double(I); %%%%%%%%%%%

/* * File: pr_loqo.h * Purpose: solves quadratic programming problem for pattern recognition * for support vectors * * Author: Alex J. Smola * Created: 10/14/97

/* * File: pr_loqo.c * Purpose: solves quadratic programming problem for pattern recognition * for support vectors * * Author: Alex J. Smola * Created: 10/14/97

function lpr_loc() % license plate recognition - car plate location based on color model % modified by ZHAO Hui, April 30th,2005 I=imread('Car.jpg'); [y,x,z]=size(I); myI=double(I); %%%%%%%%%%%

package java_cup; /** This class represents a transition in an LALR viable prefix recognition * machine. Transitions can be under terminals for non-terminals. They are * internally linked toge