Photographs taken in daily life often became blurred due to shaking,out-of-focus,changes in depth of field,and movement of photographed objects.Aiming at this problem,a double-channel cyclic image deblurring method ba...Photographs taken in daily life often became blurred due to shaking,out-of-focus,changes in depth of field,and movement of photographed objects.Aiming at this problem,a double-channel cyclic image deblurring method based on edge features was proposed.Firstly,image edge gradient operator was introduced as a threshold based on the rule that the maximum value of the image edge gradient will decrease after the blurring process,making the blurred image be divided into two channels:edge channel and non-edge channel.Secondly,a double-channel loop iteration network was designed,where the edge gradient was used in the edge channel to sample the main edge structure and bilateral filtering was used in the non-edge channel to extract the detailed texture feature information.Finally,the feature information extracted from two channels was cyclically iterated to obtain a clear image using the deblurring model with maximum a posteriori probability.The experimental results showed that the image evaluation indexes obtained by the proposed deblurring model were superior to those of other algorithms,and the edge structure and texture details of the image were effectively recovered with better performance.展开更多
The equilibrium reconstruction is important to study the tokamak plasma physical processes.To analyze the contribution of fast ions to the equilibrium,the kinetic equilibria at two time-slices in a typical H-mode disc...The equilibrium reconstruction is important to study the tokamak plasma physical processes.To analyze the contribution of fast ions to the equilibrium,the kinetic equilibria at two time-slices in a typical H-mode discharge with different auxiliary heatings are reconstructed by using magnetic diagnostics,kinetic diagnostics and TRANSP code.It is found that the fast-ion pressure might be up to one-third of the plasma pressure and the contribution is mainly in the core plasma due to the neutral beam injection power is primarily deposited in the core region.The fast-ion current contributes mainly in the core region while contributes little to the pedestal current.A steep pressure gradient in the pedestal is observed which gives rise to a strong edge current.It is proved that the fast ion effects cannot be ignored and should be considered in the future study of EAST.展开更多
Weakly supervised object localization mines the pixel-level location information based on image-level annotations.The traditional weakly supervised object localization approaches exploit the last convolutional feature...Weakly supervised object localization mines the pixel-level location information based on image-level annotations.The traditional weakly supervised object localization approaches exploit the last convolutional feature map to locate the discriminative regions with abundant semantics.Although it shows the localization ability of classification network,the process lacks the use of shallow edge and texture features,which cannot meet the requirement of object integrity in the localization task.Thus,we propose a novel shallow feature-driven dual-edges localization(DEL)network,in which dual kinds of shallow edges are utilized to mine entire target object regions.Specifically,we design an edge feature mining(EFM)module to extract the shallow edge details through the similarity measurement between the original class activation map and shallow features.We exploit the EFM module to extract two kinds of edges,named the edge of the shallow feature map and the edge of shallow gradients,for enhancing the edge details of the target object in the last convolutional feature map.The total process is proposed during the inference stage,which does not bring extra training costs.Extensive experiments on both the ILSVRC and CUB-200-2011 datasets show that the DEL method obtains consistency and substantial performance improvements compared with the existing methods.展开更多
基金supported in part by Natural Science Research Foundation of Shanxi Province(Nos.20210302123019,20210302124195,20210302124212,20210302123189)。
文摘Photographs taken in daily life often became blurred due to shaking,out-of-focus,changes in depth of field,and movement of photographed objects.Aiming at this problem,a double-channel cyclic image deblurring method based on edge features was proposed.Firstly,image edge gradient operator was introduced as a threshold based on the rule that the maximum value of the image edge gradient will decrease after the blurring process,making the blurred image be divided into two channels:edge channel and non-edge channel.Secondly,a double-channel loop iteration network was designed,where the edge gradient was used in the edge channel to sample the main edge structure and bilateral filtering was used in the non-edge channel to extract the detailed texture feature information.Finally,the feature information extracted from two channels was cyclically iterated to obtain a clear image using the deblurring model with maximum a posteriori probability.The experimental results showed that the image evaluation indexes obtained by the proposed deblurring model were superior to those of other algorithms,and the edge structure and texture details of the image were effectively recovered with better performance.
基金supported by National Key R&D Program of China under Grant No.2017YFE0300400National Natural Science Foundation of China under Grant Nos.11475220,11405218,11575248+1 种基金the National Magnetic Confinement Fusion Science Program of China under Contracts No.2014GB106001sponsored in part by Youth Innovation Promotion Association Chinese Academy of Sciences (Grant No.2016384)
文摘The equilibrium reconstruction is important to study the tokamak plasma physical processes.To analyze the contribution of fast ions to the equilibrium,the kinetic equilibria at two time-slices in a typical H-mode discharge with different auxiliary heatings are reconstructed by using magnetic diagnostics,kinetic diagnostics and TRANSP code.It is found that the fast-ion pressure might be up to one-third of the plasma pressure and the contribution is mainly in the core plasma due to the neutral beam injection power is primarily deposited in the core region.The fast-ion current contributes mainly in the core region while contributes little to the pedestal current.A steep pressure gradient in the pedestal is observed which gives rise to a strong edge current.It is proved that the fast ion effects cannot be ignored and should be considered in the future study of EAST.
基金This work was partly supported by National Natural Science Foundation of China(No.62072394)Natural Science Foundation of Hebei Province,China(No.F2021203019)Hebei Key Laboratory Project,China(No.202250701010046).
文摘Weakly supervised object localization mines the pixel-level location information based on image-level annotations.The traditional weakly supervised object localization approaches exploit the last convolutional feature map to locate the discriminative regions with abundant semantics.Although it shows the localization ability of classification network,the process lacks the use of shallow edge and texture features,which cannot meet the requirement of object integrity in the localization task.Thus,we propose a novel shallow feature-driven dual-edges localization(DEL)network,in which dual kinds of shallow edges are utilized to mine entire target object regions.Specifically,we design an edge feature mining(EFM)module to extract the shallow edge details through the similarity measurement between the original class activation map and shallow features.We exploit the EFM module to extract two kinds of edges,named the edge of the shallow feature map and the edge of shallow gradients,for enhancing the edge details of the target object in the last convolutional feature map.The total process is proposed during the inference stage,which does not bring extra training costs.Extensive experiments on both the ILSVRC and CUB-200-2011 datasets show that the DEL method obtains consistency and substantial performance improvements compared with the existing methods.
