Nanoimprint lithography (NIL) is an important nanolithography process with low cost, high throughput and high resolution. It creates patterns by mechanical deformation of imprint resist. Fabricating gratings by NIL ca...
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ISBN:
(纸本)9781424472352
Nanoimprint lithography (NIL) is an important nanolithography process with low cost, high throughput and high resolution. It creates patterns by mechanical deformation of imprint resist. Fabricating gratings by NIL can manufacture lots of replica in a fast way. Simulation on the NIL process has a vital role on choosing optimized parameters. One finite element analysis software DEFORM was used to analyze different imprint factors. Through simulation optimization, it was found that imprint temperature, pressure and time strongly affected the replication fidelity. The simulation result will guide the NIL experiment.
Combing with specific temporal information of video, this paper proposes a kind of video object tracking method based on normalized cross-correlation matching by using the high precision characteristics of normalized ...
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Combing with specific temporal information of video, this paper proposes a kind of video object tracking method based on normalized cross-correlation matching by using the high precision characteristics of normalized cross-correlation image matching. Firstly, extract video background from the temporal information of video. Then, acquire the region of moving object using background subtraction. Lastly, carry out related matching and updating towards the extracted moving object by means of normalized cross-correlation. Experimental result shows that the adaptability of our method is strong, which can well solve the tracking problems when tracking objects have scale transform. It also has good anti-interference ability and robustness, and can track moving objects accurately under the condition of noise interference, lens dithering and background mutation.
With the exponential growth of digital video resources, huge amount of videos are uploaded onto the Internet. Therefore, the Content Based Copy Detection (CBCD) issue becomes a hot research topic and has been extensiv...
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With the exponential growth of digital video resources, huge amount of videos are uploaded onto the Internet. Therefore, the Content Based Copy Detection (CBCD) issue becomes a hot research topic and has been extensively studied recently. However, most of the approaches lack the power to efficiently handle large data corpus while maintaining a good detection quality. In this paper, we propose a fast CBCD approach based on the Slice Entropy Scattergraph (SES). SES employs video spatio-temporal slices which can greatly decrease the storage and computational complexity. It is based on entropy and its deviation so as to preserve as much as the video information. Besides, SES takes advantage of a scattergraph which is succinct and efficient to plot the distribution of video content. To effectively describe SES, we introduce three descriptors: Projection Histograms, Shape Contexts and Polynomial Coefficients. The experiments on CIVR'07 Copy Detection Corpus and Video Transformation Corpus show the performance improvement of our approach both on efficiency and effectiveness.
This paper is concerned with the reliable filtering problem for network-based linear continuous-time system with sensor failures, The purpose of the addressed filtering problem is to design a filter such that the erro...
This paper is concerned with the reliable filtering problem for network-based linear continuous-time system with sensor failures, The purpose of the addressed filtering problem is to design a filter such that the error dynamics of the filtering process is stable. By using the linear matrix inequality (LMI) method, sufficient conditions are established that ensure the filter parameters are characterized by the solution to a set of LMIs. Simulation results are provided to illustrate effectiveness of the proposed method.
Multiview image registration is widely used in computer vision applications. In this paper, an approach for multiview 3D image registration based on augmented Kalman filter is proposed by taking account of various unc...
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Multiview image registration is widely used in computer vision applications. In this paper, an approach for multiview 3D image registration based on augmented Kalman filter is proposed by taking account of various uncertainties. The position and orientation of viewpoint are considered as system state. System augmentation model and system observation model are constructed. The position and orientation of each viewpoint is augmented and updated recursively. The global transformation parameters of image are computed with the state estimation of corresponding viewpoint. The proposed multiview image registration method can handle the uncertainty efficiently and the registration result is accurate and globally consistent. Some experimental results are provided to validate the performance of the proposed method.
In partial-duplicate image retrieval, images are commonly represented using Bag-of-visual-Words (BoW) built from image local features, such as SIFT. Therefore, the discriminative power of the local features is closely...
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In partial-duplicate image retrieval, images are commonly represented using Bag-of-visual-Words (BoW) built from image local features, such as SIFT. Therefore, the discriminative power of the local features is closely related with the BoW image representation and its performance in different applications. In this paper, we first propose a rotation-invariant Local Self-Similarity Descriptor (LSSD), which captures the internal geometric layouts in the local textural self-similar regions around interest points. Then we combine LSSD with SIFT to develop a multi-description of images for retrieving partial-duplicate. Finally, we formulate the Semi-Relative Entropy as the distance metric. Retrieval performance of this multi-description evaluated in the Oxford building dataset and an image corpus crawled from Google shows that the average precision achieves 11.1% and 2.8% improvement, respectively, comparing with state-of-the-art bundling feature.
By use of the properties of ant colony algorithm and genetic algorithm, a novel ant colony genetic hybrid algorithm, whose framework of hybrid algorithm is genetic algorithm, is proposed to solve the traveling salesma...
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Because of strong coupling, nonlinear, and time-varying characteristics, it is difficult to control complex spacecraft. By means of combining with controlled object dynamics and performance requirements, characteristi...
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Because of strong coupling, nonlinear, and time-varying characteristics, it is difficult to control complex spacecraft. By means of combining with controlled object dynamics and performance requirements, characteristic modeling and control approach is an effective way to solve this problem. Aimed at the flexible satellites described by using characteristic modeling approach, with the help of fuzzy rules, fuzzy dynamic characteristic modeling method and intelligent adaptive controller are designed to control this complex spacecraft. Meanwhile, based on the satellite system simulation platform, we validate the correctness and efficiency of the proposed modeling and control method by comparing with the simulation results of the other similar methods.
In recent years, dynamics model and control of space robot system are the hot topics in the research field. In this paper, a new dynamics model and control strategy of space robotic system with a flexible manipulator ...
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In recent years, dynamics model and control of space robot system are the hot topics in the research field. In this paper, a new dynamics model and control strategy of space robotic system with a flexible manipulator and a liquid fuel tank are investigated. Based on Lagrange equation method, the dynamics model of the space robotic system coupling with liquid sloshing, flexibility vibration and base movement is derived. The elastic deflection of the flexible manipulator is described by the assumed mode method and equivalent mechanical model is adopted instead of liquid sloshing under the environment of low-gravity. The inverse dynamics control algorithm combined with PD control method is performed to solve the trajectory tracking problem. Some simulation results are given to verify the effectiveness of the proposed method.
Automatic image annotation, which aims at automatically identifying and then assigning semantic keywords to the meaningful objects in a digital image, is not a very difficult task for human but has been regarded as a ...
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Automatic image annotation, which aims at automatically identifying and then assigning semantic keywords to the meaningful objects in a digital image, is not a very difficult task for human but has been regarded as a difficult and challenging problem to machines. In this paper, we present a hierarchical annotation scheme considering that generally human s visual identification to a scenery object is a rough-to-fine hierarchical process. First, the input image is segmented into multiple regions and each segmented region is roughly labeled with a general keyword using the multi-classification support vector machine. Since the results of rough annotation affect fine annotation directly, we construct the statistical contextual relationship to revise the improper labels and improve the accuracy of rough annotation. To obtain reasonable fine annotation for those roughly classified regions, we propose an active semi-supervised expectation-maximization algorithm, which can not only find the representative pattern of each fine class but also classify the roughly labeled regions into corresponded fine classes. Finally, the contextual relationship is applied again to revise the improper fine labels. To illustrate the effectiveness of the presented approaches, a prototype image annotation system is developed, the preliminary results of which showed that the hierarchical annotation scheme is effective.
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