Vehicular network technology has made substantial advancements in recent years in the field of Intelligent Transportation Systems. Vehicular Cloud Computing (VCC) has emerged as a novel paradigm with a substantial inc...
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3D segmentation has been a hot spot in numerical geometry *** the accuracy of the segmentation methods can be easily affected by the types of models because their sensitivity to different models is *** address this pr...
3D segmentation has been a hot spot in numerical geometry *** the accuracy of the segmentation methods can be easily affected by the types of models because their sensitivity to different models is *** address this problem,we propose a semi-automatic 3D mesh segmentation algorithm based on harmonic ***,our algorithm utilizes the strokes of users as constraints on the harmonic field of the mesh ***,a smooth harmonic field based on Laplacian operator and Poisson equation is *** the generated harmonic field,the correct weights are selected to further fit the geometric characteristics of the ***,we find a set of most suitable isolines on the harmonic field as the segmentation ***,a mesh density enhancement method is designed,which optimizes sub-graphs after *** results demonstrate that the effectiveness of our proposed ***,the semi-automatic 3D mesh segmentation algorithm can better understand the intention of users.
As from time to time it is impractical to ask agents to provide linear orders over all alternatives, for these partial rankings it is necessary to conduct preference completion. Specifically, the personalized preferen...
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The use of symbol attributes on the side of symbolic social networks to analyze,understand,and predict the topology,function,and dynamic behaviour of complex networks,and has important theoretical significance for per...
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The use of symbol attributes on the side of symbolic social networks to analyze,understand,and predict the topology,function,and dynamic behaviour of complex networks,and has important theoretical significance for personalized recommendations,attitude prediction,user feature analysis,and clustering and application ***,due to the huge scale of online social networks,this poses a challenge to traditional symbolic social network analysis *** on the theory of structural equilibrium,this paper studies the evolutionary dynamics of symbolic social networks,proposes the energy function of weak structural equilibrium theory,and uses the evolution of evolutionary algorithms to obtain the weak imbalance of the *** simulation experiment results show that the calculation method in this paper can get the optimal solution *** provides an idea for the study of real and complex social networks.
In recent years, many colleges and universities have set up the major of big *** biggest problem in teaching is that there is no supporting basic experimental environment,and it is difficult to deploy and configure th...
In recent years, many colleges and universities have set up the major of big *** biggest problem in teaching is that there is no supporting basic experimental environment,and it is difficult to deploy and configure the big data environment at the same time. In addition, the lack of experimental data, experimental teaching plans and experimental manuals in the experimental process makes it difficult to carry out relevant teaching. In order to reduce the cost of laboratory construction and the difficulty of learning big data, a lightweight big data experimental platform was constructed based on virtualized container technology. Through this platform, we can create a big data cluster, provide various suitable experimental environments,focus on the technology itself, and greatly improve the learning efficiency.
With the rapid development of communication technology, digital technology has been widely used in all walks of life. Nevertheless, with the wide dissemination of digital information, there are many security problems....
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Now, the highway toll system still uses a single license plate recognition, this method has a problem of inaccurate identificationFor this kind of situation, this paper put forward to increase the appearance of the ve...
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ISBN:
(纸本)9781510828087
Now, the highway toll system still uses a single license plate recognition, this method has a problem of inaccurate identificationFor this kind of situation, this paper put forward to increase the appearance of the vehicle feature information and can improve the accuracy of recognitionIn this paper, we adopt the ORB algorithm to extract the exterior feature information of the vehicle and two-way matching、RANSAC algorithms to remove mismatching pointsAt the same time, we continue to iteration the scale parameter of the affine transformation and rotation angle at the matching point as a kind of judgment, which improves the robustness of the algorithm.
Kolmogorov-Arnold Networks (KAN) is an emerging neural network architecture in machine learning. It has greatly interested the research community about whether KAN can be a promising alternative of the commonly used M...
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Simultaneous Localization and Mapping (SLAM) and Autonomous Driving are becoming increasingly more important in recent years. Point cloud-based large scale place recognition is the spine of them. While many models hav...
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This paper attacks the challenging problem of zero-example video retrieval. In such a retrieval paradigm, an end user searches for unlabeled videos by ad-hoc queries described in natural language text with no visual e...
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ISBN:
(纸本)9781728132945
This paper attacks the challenging problem of zero-example video retrieval. In such a retrieval paradigm, an end user searches for unlabeled videos by ad-hoc queries described in natural language text with no visual example provided. Given videos as sequences of frames and queries as sequences of words, an effective sequence-to-sequence cross-modal matching is required. The majority of existing methods are concept based, extracting relevant concepts from queries and videos and accordingly establishing associations between the two modalities. In contrast, this paper takes a concept-free approach, proposing a dual deep encoding network that encodes videos and queries into powerful dense representations of their own. Dual encoding is conceptually simple, practically effective and end-to-end. As experiments on three benchmarks, i.e. MSR-VTT, TRECVID 2016 and 2017 Ad-hoc Video Search show, the proposed solution establishes a new state-of-the-art for zero-example video retrieval.
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