为解决传统城市公交出行效率低、乘客体验差、一体化服务水平低的问题,创新研究了基于雄安新区的出行即服务(Mobility as a Service,MaaS)模式.首先,立足于雄安新区发展实际,分析雄安MaaS出行即服务模式的发展要求;其次,从管理架构、服...为解决传统城市公交出行效率低、乘客体验差、一体化服务水平低的问题,创新研究了基于雄安新区的出行即服务(Mobility as a Service,MaaS)模式.首先,立足于雄安新区发展实际,分析雄安MaaS出行即服务模式的发展要求;其次,从管理架构、服务模式和智能系统角度总结国际先进MaaS建设经验;最后,阐述雄安新区在MaaS管理架构设计、公交服务模式构建、MaaS出行平台等方面的建设经验,并提出未来发展思考.展开更多
Synthetic aperture radar（SAR）image is severely affected by multiplicative speckle noise,which greatly complicates the edge detection.In this paper,by incorporating the discontinuityadaptive Markov random feld（DAMRF...Synthetic aperture radar（SAR）image is severely affected by multiplicative speckle noise,which greatly complicates the edge detection.In this paper,by incorporating the discontinuityadaptive Markov random feld（DAMRF）and maximum a posteriori（MAP）estimation criterion into edge detection,a Bayesian edge detector for SAR imagery is accordingly developed.In the proposed detector,the DAMRF is used as the a priori distribution of the local mean reflectivity,and a maximum a posteriori estimation of it is thus obtained by maximizing the posteriori energy using gradient-descent method.Four normalized ratios constructed in different directions are computed,based on which two edge strength maps（ESMs）are formed.The fnal edge detection result is achieved by fusing the results of two thresholded ESMs.The experimental results with synthetic and real SAR images show that the proposed detector could effciently detect edges in SAR images,and achieve better performance than two popular detectors in terms of Pratt＇s fgure of merit and visual evaluation in most cases.展开更多
文摘为解决传统城市公交出行效率低、乘客体验差、一体化服务水平低的问题,创新研究了基于雄安新区的出行即服务(Mobility as a Service,MaaS)模式.首先,立足于雄安新区发展实际,分析雄安MaaS出行即服务模式的发展要求;其次,从管理架构、服务模式和智能系统角度总结国际先进MaaS建设经验;最后,阐述雄安新区在MaaS管理架构设计、公交服务模式构建、MaaS出行平台等方面的建设经验,并提出未来发展思考.
基金supported National Natural Science Foundation of China (No.61102167)
文摘Synthetic aperture radar（SAR）image is severely affected by multiplicative speckle noise,which greatly complicates the edge detection.In this paper,by incorporating the discontinuityadaptive Markov random feld（DAMRF）and maximum a posteriori（MAP）estimation criterion into edge detection,a Bayesian edge detector for SAR imagery is accordingly developed.In the proposed detector,the DAMRF is used as the a priori distribution of the local mean reflectivity,and a maximum a posteriori estimation of it is thus obtained by maximizing the posteriori energy using gradient-descent method.Four normalized ratios constructed in different directions are computed,based on which two edge strength maps（ESMs）are formed.The fnal edge detection result is achieved by fusing the results of two thresholded ESMs.The experimental results with synthetic and real SAR images show that the proposed detector could effciently detect edges in SAR images,and achieve better performance than two popular detectors in terms of Pratt＇s fgure of merit and visual evaluation in most cases.
