We introduce a class of set-theoretic operators on a tolerance space that models the process of minimal belief contraction, and therefore a natural process of iterated contraction can be defined. We characterize the c...
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The firefly algorithm (FA) is a new population-based metaheuristic bioinspired on the behavior of the flashing characteristics of fireflies. As a population-based algorithm, the FA suffers from large execution times s...
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The electoral system is vital to the democratic process. Several countries have adopted different mechanisms for the electoral process, from paper ballots to electronic voting machines and online voting. There are sev...
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Porous, nanostructured silver samples were produced using a direct-write method where a nanoparticle aerosol consisting of particles with a mean size of approximately 5 nm were accelerated to speeds of approximately 1...
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Multi-hole defect (MHD) photonic crystal cavities functionalized with in situ synthesized DNA bioreceptors are demonstrated for biosensing applications. By significantly increasing light interaction with target biomol...
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This paper proposes an incremental, structural and contextual validation method for Nested Context Language (NCL) documents. As part of the proposed method, we define a declarative metalanguage to ensure low coupling ...
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In this paper, we will investigate a more challenging vehicle matching problem. The problem is formulated as invariant image feature matching among opposite viewpoints of cameras, i.e. complementary object matching. F...
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ISBN:
(纸本)9781467361989
In this paper, we will investigate a more challenging vehicle matching problem. The problem is formulated as invariant image feature matching among opposite viewpoints of cameras, i.e. complementary object matching. For example, a front vehicle object may be given as a query to retrieve a rear vehicle object of the same vehicle. To solve the complementary object matching, invariant image feature is first extracted based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, the ASIFT feature is expanded via a special vehicle database. As a result, cross-camera vehicle matching with the help of complementary part can be greatly improved. Experimental results demonstrate the effectiveness of the proposed algorithm and the feasibility to video forensics applications.
The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect a...
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ISBN:
(纸本)9781479900145
The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect and track each vehicle within a large area, which can be applied to video forensics. For example, a suspected vehicle can be automatically identified for mining digital criminal evidences from a large amount of video data. In this paper, we propose an efficient cross-camera vehicle tracking technique via affine invariant object matching. More specifically, we formulate the problem as invariant image feature matching among different viewpoints of cameras. To achieve vehicle matching, we first extract invariant image feature based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, to improve the accuracy of ASIFT feature matching between images from different viewpoints, we propose to efficiently match feature points based on our observed spatially invariant property of ASIFT, as well as the min-hash technique. As a result, cross-camera vehicle tracking can be efficiently and accurately achieved. Experimental results demonstrate the efficacy of the proposed algorithm and the feasibility to video forensics applications.
Porous, nanostructured silver samples were produced using a direct-write method where a nanoparticle aerosol consisting of particles with a mean size of approximately 5 nm were accelerated to speeds of approximately 1...
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Porous, nanostructured silver samples were produced using a direct-write method where a nanoparticle aerosol consisting of particles with a mean size of approximately 5 nm were accelerated to speeds of approximately 1000 m/sec and impacted onto a translating substrate [1]. The impacting particles have sufficient energy to stick to the substrate, allowing patterned thick films to be directly written from the aerosol without a mask. Unlike other low temperature processing routes for achieving patterned films, no organics are added that can interfere with postdeposition processing. Typical films are 5- 100 μm thick, up to several centimeters long, and have an as-deposited relative densities as high as 70% of bulk Ag. Compression tests were carried out in steps at room temperature and at 150°C under constant displacement rates. Local strain and densification were measured by optical profilometry between each compression step. The results can be used as a starting point to better understand the mechanisms that govern plasticity, creep, and sintering in nanostructured, porous silver at low processing temperatures.
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