This paper introduces the identification of the defects on the fabric by using two-double neural network and wavelet analysis. The purpose is to fit for the automatic cloth inspection system and to avoid the disadvant...This paper introduces the identification of the defects on the fabric by using two-double neural network and wavelet analysis. The purpose is to fit for the automatic cloth inspection system and to avoid the disadvantages of traditional human inspection. Firstly, training the normal fabric to acquire its characteristics and then using the BP neural network to tell the normal fabric apart from the one with defects. Secondly, doing the two-dimeusional discrete wavelet transformation based on the image of the defects, then wiping off the proper characteristics of the fabric, and identifying the defects utilizing the trained BP neural network. It is proved that this method is of high speed and accuracy. It comes up to the requirement of automatic cloth inspection.展开更多
The quantitative trait loci (QTLs) for cold tolerance relative characters were identified with microsatellite markers.Ten QTLs located on chromosome 1, 3, 4, 5, 6, 8, 9, 11(two)and 12 were detected for seedling height...The quantitative trait loci (QTLs) for cold tolerance relative characters were identified with microsatellite markers.Ten QTLs located on chromosome 1, 3, 4, 5, 6, 8, 9, 11(two)and 12 were detected for seedling height at different low temperature. Only 2 of these were detected at the same locus at four environments, 1 was significant at three environments, 6 were significant at two environments and 1 was significant at one environment. Seven QTLs located on chromosome 1(two), 2(two),5,6,8 were found for low temperature chlorosis resistance and five QTLs located on chromosome 3, 4, 7, 8, 11 resistant to chilling injury. The amount of variation explained by individual QTL ranged from 4.85%to 49.34%. There was no linkage relationship among the three characters, which indicates seedling cold tolerance is a complex character and is controlled by different QTLs.展开更多
文摘This paper introduces the identification of the defects on the fabric by using two-double neural network and wavelet analysis. The purpose is to fit for the automatic cloth inspection system and to avoid the disadvantages of traditional human inspection. Firstly, training the normal fabric to acquire its characteristics and then using the BP neural network to tell the normal fabric apart from the one with defects. Secondly, doing the two-dimeusional discrete wavelet transformation based on the image of the defects, then wiping off the proper characteristics of the fabric, and identifying the defects utilizing the trained BP neural network. It is proved that this method is of high speed and accuracy. It comes up to the requirement of automatic cloth inspection.
文摘The quantitative trait loci (QTLs) for cold tolerance relative characters were identified with microsatellite markers.Ten QTLs located on chromosome 1, 3, 4, 5, 6, 8, 9, 11(two)and 12 were detected for seedling height at different low temperature. Only 2 of these were detected at the same locus at four environments, 1 was significant at three environments, 6 were significant at two environments and 1 was significant at one environment. Seven QTLs located on chromosome 1(two), 2(two),5,6,8 were found for low temperature chlorosis resistance and five QTLs located on chromosome 3, 4, 7, 8, 11 resistant to chilling injury. The amount of variation explained by individual QTL ranged from 4.85%to 49.34%. There was no linkage relationship among the three characters, which indicates seedling cold tolerance is a complex character and is controlled by different QTLs.
