The optimized color space is searched by using the wavelet scattering network in the KTH_TIPS_COL color image database for image texture classification. The effect of choosing the color space on the classification acc...The optimized color space is searched by using the wavelet scattering network in the KTH_TIPS_COL color image database for image texture classification. The effect of choosing the color space on the classification accuracy is investigated by converting red green blue （RGB） color space to various other color spaces. The results show that the classification performance generally changes to a large degree when performing color texture classification in various color spaces, and the opponent RGB-based wavelet scattering network outperforms other color spaces-based wavelet scattering networks. Considering that color spaces can be changed into each other, therefore, when dealing with the problem of color texture classification, converting other color spaces to the opponent RGB color space is recommended before performing the wavelet scattering network.展开更多
The reconstruction with minimized dispersion and controllable dissipation(MDCD) optimizes dispersion and dissipation separately and shows desirable properties of both dispersion and dissipation.A low dispersion finite...The reconstruction with minimized dispersion and controllable dissipation(MDCD) optimizes dispersion and dissipation separately and shows desirable properties of both dispersion and dissipation.A low dispersion finite volume scheme based on MDCD reconstruction is proposed which is capable of handling flow discontinuities and resolving a broad range of length scales.Although the proposed scheme is formally second order accurate,the optimized dispersion and dissipation make it very accurate and robust so that the rich flow features encountered in practical engineering applications can be handled properly.A number of test cases are computed to verify the performances of the proposed scheme.展开更多
基金The National Basic Research Program of China(No.2011CB707904)the National Natural Science Foundation of China(No.61201344,61271312,11301074)+1 种基金the Natural Science Foundation of Jiangsu Province(No.BK2012329)the Specialized Research Fund for the Doctoral Program of Higher Education(No.20110092110023,20120092120036)
文摘The optimized color space is searched by using the wavelet scattering network in the KTH_TIPS_COL color image database for image texture classification. The effect of choosing the color space on the classification accuracy is investigated by converting red green blue （RGB） color space to various other color spaces. The results show that the classification performance generally changes to a large degree when performing color texture classification in various color spaces, and the opponent RGB-based wavelet scattering network outperforms other color spaces-based wavelet scattering networks. Considering that color spaces can be changed into each other, therefore, when dealing with the problem of color texture classification, converting other color spaces to the opponent RGB color space is recommended before performing the wavelet scattering network.
基金supported by the National Natural Science Foundation of China (Grant Nos. 11172153 and 10932005)
文摘The reconstruction with minimized dispersion and controllable dissipation(MDCD) optimizes dispersion and dissipation separately and shows desirable properties of both dispersion and dissipation.A low dispersion finite volume scheme based on MDCD reconstruction is proposed which is capable of handling flow discontinuities and resolving a broad range of length scales.Although the proposed scheme is formally second order accurate,the optimized dispersion and dissipation make it very accurate and robust so that the rich flow features encountered in practical engineering applications can be handled properly.A number of test cases are computed to verify the performances of the proposed scheme.
