http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Biao Wang,Seokkeun Choi,Younggi Byun,Soungki Lee,Jaewan Choi IEEE 2015 IEEE geoscience and remote sensing letters Vol.12 No.5
<P>In this letter, we present a method for unsupervised change detection based on the cross-sharpening of multitemporal images and image segmentation. Our method effectively reduces the change detection errors caused by relief or spatial displacement between multitemporal images with different acquisition angles. A total of four cross-sharpened images, including two general pansharpened images, were generated. Then, two pairs of cross-sharpened images were analyzed using change detection indexes. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation.</P>
A Matrix Approach for the Static Correction Problem of Asynchronous Sequential Machines
Biao Wang,Jun-e Feng 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.2
This paper investigates the static correction problem of asynchronous sequential machines (ASMs) via semi-tensor product (STP) of matrices. For an input/state ASM, the static correction problem is to find a static state feedback controller to solve model matching. This controller contains no memory units and consists of only some logic gates. First, by STP method, two algebraic forms are derived to describe the dynamics of an input/state ASM and the function of a static state feedback controller, respectively. Then, as two special cases, the static state feedback controllers for no mismatch and only one mismatch are given. Based on these two cases and analyzing reachability of an ASM, a static state feedback controller design for model matching is presented. Moreover, the number of working points this controller contains is the least. Finally, the proposed method is applied to a simple home security system.
Biao Wang,Yan Huang,Yonghong Wang,Peizheng Yan,Qiaosheng Pan 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.5
The mechanical structures of micro-electro-mechanical systems (MEMS) are composed of different types of microstructures, and their mechanical properties are very important for the realisation and reliability of the system performance. One of the key problems in measuring the mechanical properties is the design and implementation of micro-nano displacement driving mechanisms. This paper describes a mechanism that adopts a two-level loading strategy, fast approach, and precise bending displacement loading structures, and has a theoretical analysis and optimal design based on optimal targets of resistance and displacement. The results show that the relative error is 6.98 % for the fast-approaching structure experiment and its optimal simulation and 4.26 % for the precise bending displacement loading structure (PBLS) experiment and its optimal simulation. The optimised micro-nano displacement loading mechanism can achieve optimal output performance under existing constraints.
융합평가 지수에 따른 고해상도 위성영상 기반 변화탐지 정확도의 비교평가
Wang Biao,최석근(Choi, Seok Geun),최재완(Choi, Jae Wan),양성철(Yang, Sung Chul),변영기(Byun, Young Gi),박경식(Park, Kyeong Sik) 대한공간정보학회 2013 대한공간정보학회지 Vol.21 No.2
변화탐지 기법은 위성영상의 활용 및 국토 모니터링에 있어서 필수적인 알고리즘이다. 그러나, 변화탐지 기법을 고해상도 위성영상에 적용할 경우, 다시기 영상 간의 기하학적 차이 등에 의하여 변화탐지 정확도가 저하될 수 있다. 본 연구에서는 효과적인 위성영상의 변화탐지를 위하여 기존의 융합 영상 평가지수를 활용하고자 한다. 또한, 기존의 다시기 위성영상을 활용한 일반적인 변화탐지 기법과 교차융합영상을 이용한 변화탐지 결과를 비교하여, 다시기 고해상도 위성영상에 적합한 변화탐지 기법을 제안하고자 한다. 이를 위해, 융합영상 평가 지수인 ERGAS, UIQI, SAM를 무감독 변화탐지 기법에 적용하고 기존의 CVA를 이용한 변화탐지 기법의 결과와 비교하였다. 또한, 영상융합 기법에 따른 고해상도 위성영상 변화탐지 정확도를 평가하여 고해상도 위성영상의 무감독 변화탐지에서 발생할 수 있는 기하학적 오차를 최소화할 수 있는 방법을 분석하였다. 실험결과, 교차융합영상과 ERGAS 지수를 활용한 변화탐지 기법이 기존 기법과 비교하여 상대적으로 높은 변화지역 탐지 가능성을 가지는 것을 확인할 수 있었다. Change detection technique is essential to various applications of Very High-Resolution(VHR) satellite imagery and land monitoring. However, change detection accuracy of VHR satellite imagery can be decreased due to various geometrical dissimilarity. In this paper, the existing fusion evaluation indexes were revised and applied to improve VHR imagery based change detection accuracy between multi-temporal images. In addition, appropriate change detection methodology of VHR images are proposed through comparison of general change detection algorithm with cross-sharpened image based change detection algorithm. For these purpose, ERGAS, UIQI and SAM, which were representative fusion evaluation index, were applied to unsupervised change detection, and then, these were compared with CVA based change detection result. Methodologies for minimizing the geometrical error of change detection algorithm are analyzed through evaluation of change detection accuracy corresponding to image fusion method, also. The experimental results are shown that change detection accuracy based on ERGAS index by using cross-sharpened images is higher than these based on other estimation index by using general fused image.