The Little Green BATS is the first and so far only Dutch team in the 3D simulation league. We are a group of graduate students from the department of AI at the University of Groningen, The Netherlands. Our team name is derived from the fact that the first 3D agents in the league were balls and from the very philosophical observation that Balls Are Truly Spheres (BATS). This abbreviation reminded us of our favorite song Little Green Bag by The George Baker SElection and so the whole team name was born. We entered the competition for the first time at the 10th edition of RoboCup at Bremen, Germany. unfortunately our hard work didn t pay off that time: already in the second round we got eliminated. However, after this we had a good base to build upon and the good time we had at the event and the nice community inspired us to continue and work hard for another year. This turned out to be defiantly worth it, because in 2007 in Atlanta we managed to become vice world champions!
標簽： simulation the Little league
上傳時間： 2014-12-07
上傳用戶：youlongjian0
hh lecture has based hardware, embedded development environment construction, embedded programme SElection, embedded industry overview and so on.
標簽： embedded construction development environment
上傳時間： 2013-12-21
上傳用戶：冇尾飛鉈
This sample is a simple example on how to perform a glow effect by rendering into an arbitrary size Frame Buffer Object (FBO). The Glow effect is performed on a specific part of the screen and can be done only on specific objects of the scene. You can imagine using such a postprocessing effect in CAD/DCC to emphasize some items from a SElection or picking for example.
標簽： arbitrary rendering example perform
上傳時間： 2014-01-03
上傳用戶：liuchee
OTSU Gray-level image segmentation using Otsu s method. Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes by means of Otsu s n-thresholding method (Otsu N, A Threshold SElection Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern. 9:62-66 1979). Thresholds are computed to maximize a separability criterion of the resultant classes in gray levels. OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the corresponding Iseg is therefore a binary image. The pixel values for Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ... [Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability criterion within the range [0 1]. Zero is obtained only with images having less than n gray level, whereas one (optimal value) is obtained only with n-valued images.
標簽： OTSU segmentation Gray-level segmented
上傳時間： 2017-04-24
上傳用戶：yuzsu
how to add arrays * Use of const (constant) values. * Creation of vectors. * Passing vectors as function arguments. * Reading from files of unknown size (monitoring istream status). * Repetitive structures (while and for loops). * The increment operators (++). * SElection structures (if-else statements). * Use of the .size, .empty, .begin, .insert, .erase, .resize, .clear and .swap vector class member functions.
標簽： Creation constant Passing vectors
上傳時間： 2017-04-25
上傳用戶：1079836864
The advantages of automation can be exploited in order to solve or to minimize the needs of manual approach. In order to support the development of survey accurate cadastral system, an automatic programming approach will be adopted. Database SElection system will conduct several outliers integrity checking, rebuild cadastral spatial topology (cadastral lot) and make selfcorrection procedures based on cadastral survey concepts and mathematical model respective to the cadastral lots selected. This is to ensure that all cadastral lots are kept in a closed polygon and provide accurate and "clean" cadastral information.. This system was developed in windows environment.
標簽： advantages automation exploited minimize
上傳時間： 2017-04-29
上傳用戶：520
為求解大規模TSP 問題,提出了并行人工免疫系統的塔式主從模型( Towerlike Master2Slave Model , TMSM) ,和基于TMSM的并行免疫記憶克隆選擇算法(Parallel Immune Memory Clonal SElection Algorithm ,PIMCSA) .
標簽： TMSM Master2Slave Towerlike Paralle
上傳時間： 2013-12-18
上傳用戶：guanliya
Sensors and Transducers is highly readable text which provides a unique introduction to the SElection and application of sensors, transducers and switches.
標簽： introduction Transducers readable provides
上傳時間： 2014-01-02
上傳用戶：四只眼
Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic model SElection tool for C-SVM classification. This document explains the use of libsvm.
標簽： classification easy-to-use regression and
上傳時間： 2017-06-24
上傳用戶：253189838
Implementations of different methods of sorting: BinaryInsertions.pas BubbleSort.pas HeapSort.pas InsertionBorder.pas InsertionSort.pas modifbubble.pas qsort.pas quicksort.pas SElection.pas Shaker.pas shell.pas
標簽： BinaryInsertions Implementations BubbleSort different
上傳時間： 2017-06-28
上傳用戶：dapangxie
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