CLM_PR
所属分类：图形图像处理
开发工具：matlab
文件大小：67335KB
下载次数：7
上传日期：2016-11-29 10:40:38
上 传 者：
战斗
说明： 对图像进行建模，利用有效的码书更少模型，很好的算法。
(Towards Effective Codebookless Model for Image)
文件列表:
CLM_PR (0, 2016-04-06)
CLM_PR\classifier (0, 2016-04-06)
CLM_PR\classifier\get_data_label.m (1582, 2016-04-06)
CLM_PR\classifier\random_split_training_test.m (1550, 2016-04-06)
CLM_PR\classifier\SVMforClassification.m (3744, 2016-04-06)
CLM_PR\classifier\svmpredict.mexw64 (23040, 2015-03-21)
CLM_PR\classifier\svmtrain.mexw64 (58880, 2015-03-21)
CLM_PR\classifier\SVM_training_test.m (6969, 2014-07-21)
CLM_PR\common (0, 2016-04-06)
CLM_PR\common\plow_expriments.m (2346, 2016-04-06)
CLM_PR\common\plow_features.m (1574, 2016-04-06)
CLM_PR\common\res_summary.m (553, 2016-04-02)
CLM_PR\common\sp_make_dir.m (223, 2008-12-10)
CLM_PR\DimRed (0, 2016-04-07)
CLM_PR\DimRed\DimensionRed.m (2612, 2016-04-06)
CLM_PR\DimRed\DRsublib.m (3077, 2016-04-06)
CLM_PR\DimRed\lda.m (2398, 2010-11-03)
CLM_PR\DimRed\LinPCA.m (1345, 2016-04-01)
CLM_PR\DimRed\lrsvm.m (3180, 2016-04-06)
CLM_PR\DimRed\makefullwj.m (685, 2014-11-03)
CLM_PR\DimRed\mexLasso.m (2249, 2010-07-30)
CLM_PR\DimRed\mexLasso.mexw32 (1520640, 2010-02-22)
CLM_PR\DimRed\mexLasso.mexw64 (182272, 2012-09-15)
CLM_PR\DimRed\processingdata.m (1769, 2016-04-06)
CLM_PR\DimRed\Rotated_SR.m (1118, 2014-09-17)
CLM_PR\DimRed\setprms.m (1126, 2014-10-28)
CLM_PR\DimRed\sp_dist2.m (979, 2009-01-17)
CLM_PR\DimRed\testDR.m (884, 2014-09-19)
CLM_PR\feaextra (0, 2016-04-06)
CLM_PR\feaextra\compute_shape_invariant_feats.m (10881, 2014-09-16)
CLM_PR\feaextra\Contents.m (1248, 2010-03-17)
CLM_PR\feaextra\DefaultVal.m (1258, 2012-08-01)
CLM_PR\feaextra\enrichments_feats.m (8386, 2015-04-10)
CLM_PR\feaextra\FbApply2d.m (1613, 2008-07-01)
CLM_PR\feaextra\FbCrop.m (1214, 2008-07-01)
CLM_PR\feaextra\FbDoG.mat (276960, 2008-07-01)
CLM_PR\feaextra\FbGabor.mat (307712, 2008-07-01)
CLM_PR\feaextra\FbMake.m (6951, 2008-11-17)
CLM_PR\feaextra\FbReconstruct2d.m (3445, 2008-07-01)
CLM_PR\feaextra\FbVisualize.m (1754, 2008-07-01)
... ...
% This is a demo code to evaluate the proposed codebookless model (CLM) using
% the Flickr material database.
%
% For theoretical and technical details, please refer to the following paper:
%
% Qilong Wang, Peihua Li, Wangmeng Zuo, and Lei Zhang. Towards Effective
% Codebookless Model for Image Classification. Pattern Recognition, 2016.
% DOI: 10.1016/j.patcog.2016.03.004
%
% Please cite the paper above if you use the code:
%
% For questions, please conact: Qilong Wang (Email: qlwang at mail dot dlut dot edu dot cn),
% Peihua Li (Email: peihuali at dlut dot edu dot cn)
%
% The software is provided ''as is'' and without warranty of any kind,
% experess, implied or otherwise, including without limitation, any
% warranty of merchantability or fitness for a particular purpose.
% The computation of SIFT features depended on VLFeat package, which was self-contained in our code.
% Usage of VLFeat package, please cite the following bibtex:
%
% @misc{vedaldi08vlfeat,
% Author = {A. Vedaldi and B. Fulkerson},
% Title = {{VLFeat}: An Open and Portable Library
% of Computer Vision Algorithms},
% Year = {2008},
% Howpublished = {\url{http://www.vlfeat.org/}}
%
% The Flickr material database was self-contained in our code.
% Usage of Flickr material database, please cite the following paper:
%
% L. Haran, R. Rosenholtz, and E. H. Adelson. Material perception:
% What can you see in a brief glance? Journal of Vision, 9(8):784, 2009.
%
% For classification, we employ LibSVM package which was self-contained in our code.
% Usage of Flickr material database, please cite the following paper:
% C.-C. Chang and C.-J. Lin. LIBSVM: A library for support vector machines.
% ACM TIST, 2(3):27, 2011.
%
% Please run 'Run_demo_fmd.m' to evaluate the proposed codebookless model.
% Our demo is programmed with Matlab R2014 on Windows ***bit OS, and runs on
% a PC equipped with 32G RAM.
%
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