A Pyramidal Morphology Algorithm is developed for speckle reduction of SARimages in this paper. For reducing the loss of information in the pyramidal algorithm for morphologyprocessing, in this modified algorithm, the...A Pyramidal Morphology Algorithm is developed for speckle reduction of SARimages in this paper. For reducing the loss of information in the pyramidal algorithm for morphologyprocessing, in this modified algorithm, the sub-images are processed parallel in the downsamplingoperation and the sub-images are reconstructed in the upsampling operation. It can be applied toimage filtering parallel. After analysis the computer simulations show that these two kinds offilters are both effective in speckle reduction of SAR images. The modified parallel algorithm doesbetter than the original algorithm and Lee filter on some characteristics.展开更多
Soybean leaf morphology is one of the most important morphological and biological characteristics of soybean.The germplasm gene differences of soybeans can lead to different phenotypic traits,among which soybean leaf ...Soybean leaf morphology is one of the most important morphological and biological characteristics of soybean.The germplasm gene differences of soybeans can lead to different phenotypic traits,among which soybean leaf morphology is an important parameter that directly reflects the difference in soybean germplasm.To realize the morphological classification of soybean leaves,a method was proposed based on deep learning to automatically detect soybean leaves and classify leaf morphology.The morphology of soybean leaves included lanceolate,oval,ellipse and round.First,an image collection platform was designed to collect images of soybean leaves.Then,the feature pyramid networks–single shot multibox detector(FPN-SSD)model was proposed to detect the top leaflets of soybean leaves on the collected images.Finally,a classification model based on knowledge distillation was proposed to classify different morphologies of soybean leaves.The obtained results indicated an overall classification accuracy of 0.956 over a private dataset of 3200 soybean leaf images,and the accuracy of classification for each morphology was 1.00,0.97,0.93 and 0.94.The results showed that this method could effectively classify soybean leaf morphology and had great application potential in analyzing other phenotypic traits of soybean.展开更多
The shear failure of intact rock under thermo-mechanical(TM)coupling conditions is common,such as in enhanced geothermal mining and deep mine construction.Under the effect of a continuous engineering disturbance,shear...The shear failure of intact rock under thermo-mechanical(TM)coupling conditions is common,such as in enhanced geothermal mining and deep mine construction.Under the effect of a continuous engineering disturbance,shear-formed fractures are prone to secondary instability,posing a severe threat to deep engineering.Although numerous studies regarding three-dimensional(3D)morphologies of fracture surfaces have been conducted,the understanding of shear-formed fractures under TM coupling conditions is limited.In this study,direct shear tests of intact granite under various TM coupling conditions were conducted,followed by 3D laser scanning tests of shear-formed fractures.Test results demonstrated that the peak shear strength of intact granite is positively correlated with the normal stress,whereas it is negatively correlated with the temperature.The internal friction angle and cohesion of intact granite significantly decrease with an increase in the temperature.The anisotropy,roughness value,and height of the asperities on the fracture surfaces are reduced as the normal stress increases,whereas their variation trends are the opposite as the temperature increases.The macroscopic failure mode of intact granite under TM coupling conditions is dominated by mixed tensileeshear and shear failures.As the normal stress increases,intragranular fractures are developed ranging from a local to a global distribution,and the macroscopic failure mode of intact granite changes from mixed tensileeshear to shear failure.Finally,3D morphological characteristics of the asperities on the shear-formed fracture surfaces were analyzed,and a quadrangular pyramid conceptual model representing these asperities was proposed and sufficiently verified.展开更多
基金the National Natural Science Foundation of Jiangsu Province.China.( No.BK2 0 0 10 47)
文摘A Pyramidal Morphology Algorithm is developed for speckle reduction of SARimages in this paper. For reducing the loss of information in the pyramidal algorithm for morphologyprocessing, in this modified algorithm, the sub-images are processed parallel in the downsamplingoperation and the sub-images are reconstructed in the upsampling operation. It can be applied toimage filtering parallel. After analysis the computer simulations show that these two kinds offilters are both effective in speckle reduction of SAR images. The modified parallel algorithm doesbetter than the original algorithm and Lee filter on some characteristics.
基金Supported by Heilongjiang Province Philosophy and Social Science Research Planning Project(17TQB059)。
文摘Soybean leaf morphology is one of the most important morphological and biological characteristics of soybean.The germplasm gene differences of soybeans can lead to different phenotypic traits,among which soybean leaf morphology is an important parameter that directly reflects the difference in soybean germplasm.To realize the morphological classification of soybean leaves,a method was proposed based on deep learning to automatically detect soybean leaves and classify leaf morphology.The morphology of soybean leaves included lanceolate,oval,ellipse and round.First,an image collection platform was designed to collect images of soybean leaves.Then,the feature pyramid networks–single shot multibox detector(FPN-SSD)model was proposed to detect the top leaflets of soybean leaves on the collected images.Finally,a classification model based on knowledge distillation was proposed to classify different morphologies of soybean leaves.The obtained results indicated an overall classification accuracy of 0.956 over a private dataset of 3200 soybean leaf images,and the accuracy of classification for each morphology was 1.00,0.97,0.93 and 0.94.The results showed that this method could effectively classify soybean leaf morphology and had great application potential in analyzing other phenotypic traits of soybean.
基金supported by the National Natural Science Foundation of China(Grant No.51974173)the Natural Science Foundation of Shandong Province,China(Grant No.ZR2020QD122).
文摘The shear failure of intact rock under thermo-mechanical(TM)coupling conditions is common,such as in enhanced geothermal mining and deep mine construction.Under the effect of a continuous engineering disturbance,shear-formed fractures are prone to secondary instability,posing a severe threat to deep engineering.Although numerous studies regarding three-dimensional(3D)morphologies of fracture surfaces have been conducted,the understanding of shear-formed fractures under TM coupling conditions is limited.In this study,direct shear tests of intact granite under various TM coupling conditions were conducted,followed by 3D laser scanning tests of shear-formed fractures.Test results demonstrated that the peak shear strength of intact granite is positively correlated with the normal stress,whereas it is negatively correlated with the temperature.The internal friction angle and cohesion of intact granite significantly decrease with an increase in the temperature.The anisotropy,roughness value,and height of the asperities on the fracture surfaces are reduced as the normal stress increases,whereas their variation trends are the opposite as the temperature increases.The macroscopic failure mode of intact granite under TM coupling conditions is dominated by mixed tensileeshear and shear failures.As the normal stress increases,intragranular fractures are developed ranging from a local to a global distribution,and the macroscopic failure mode of intact granite changes from mixed tensileeshear to shear failure.Finally,3D morphological characteristics of the asperities on the shear-formed fracture surfaces were analyzed,and a quadrangular pyramid conceptual model representing these asperities was proposed and sufficiently verified.
