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检索条件"任意字段=5th International Conference on Fun with Algorithms"

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5th international conference on Scale Space and Variational Methods in Computer Vision, SSVM 2015

5th International Conference on Scale Space and Variational ...

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5th international conference on Scale Space and Variational Methods in Computer Vision, SSVM 2015

ISBN: (纸本)9783319184609

the proceedings contain 56 papers. the special focus in this conference is on Scale space and variational methods in computer vision. the topics include: Scale-Space theory for auditory signals;spectral representations of one-homogeneous functionals;the morphological equivalents of relativistic and alpha-scale-spaces;new approximation of a scale space kernel on SE(3) and applications in neuroimaging;partial differential equations of bivariate median filters;fundamentals of non-local total variation spectral theory;morphological scale-space operators for images supported on point clouds;separable time-causal and time-recursive spatio-temporal receptive fields;a linear scale-space theory for continuous nonlocal evolutions;bilevel image denoising using gaussianity tests;on debiasing restoration algorithms: applications to total-variation and nonlocal-means;cartoon-texture-noise decomposition with transport norms;compressing images with diffusion- and exemplar-based inpainting;some nonlocal filters formulation using functional rearrangements;total variation restoration of images corrupted by poisson noise with iterated conditional expectations;regularization with sparse vector fields: from image compression to TV-type reconstruction;solution-driven adaptive total variation regularization;artifact-free variational MPEG decompression;probabilistic correlation clustering and image partitioning using perturbed multicuts;optimizing the relevance-redundancy tradeoff for efficient semantic segmentation;convex color image segmentation with optimal transport distances;piecewise geodesics for vessel centerline extraction and boundary delineation with application to retina segmentation;unsupervised learning using the tensor voting graph;interactive multi-label segmentation of RGB-D images and fast minimization of region-based active contours using the shape hessian of the energy.

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A Modified K-Nearest Neighbor Algorithm to Handle Uncertain Data

A Modified K-Nearest Neighbor Algorithm to Handle Uncertain ...

引用

international conference on IT Convergence and Security (ICITCS)

作者： Rashmi Agrawal Babu Ram Faulty of Engineering & Technology Manav Rachna International University Faridabad India Faculty of Computer Applications Manav Rachna International University Faridabad India

Classification is an important technique in data mining. the K-Nearest neighbor (K-NN) algorithm is a memory based algorithm and is capable of producing satisfactory results when applied on certain data but the distance measures used in this algorithm is not capable of handling the data sets containing the uncertain attribute values. Data uncertainty is common in real word applications. In this paper we have proposed an effective distance measure and modified K-NN which can be applied on the data sets containing uncertain numerical attributes and gives satisfactory results.

关键词： Classification algorithms Uncertainty Measurement Training Prediction algorithms Accuracy Probabilistic logic

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A personalized recommendation algorithm based on Hadoop

A personalized recommendation algorithm based on Hadoop

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international conference on Electronics Information and Emergency Communication

作者： Hao Huang Jianqing Huang Sotirios G. Ziavras Yaojie Lu School of Information Technology University of International Business and Economics Beijing PR China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark U.S.A.

BDM-NBI algorithm is proposed at this paper. It focuses on the analysis of a personalized recommendation algorithm that utilizes a weighted bipartite graph suitable for processing big data. Our algorithm adopts bipartite graph partitioning using a vertex separator method that partitions a high-dimensional sparse matrix into a pseudo-block based diagonal matrix. then, the recommendation algorithm analyzes all weighted sub-matrices in parallel. We produce the global recommendation weighted matrix by merging all of the sub-matrices in parallel. Experiments with Hadoop show that our algorithm has good approximation for small matrices and excellent scalability.

关键词： Partitioning algorithms Sparse matrices Couplings Algorithm design and analysis Approximation algorithms Filtering Motion pictures

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Research on the Realization and the Correction Method of Velocity Interpolation Algorithm for the Quadratic Curve

Research on The Realization and The Correction Method of Vel...

引用

2015 5th international conference on Computer Sciences and Automation Engineering(ICCSAE 2015)

作者： Chi Tang Ying Li School of Mechanical and Power Engineering East China University of Science and Technology

ISBN: (纸本)9781510818972

Aiming at the problem of low efficiency and low accuracy of traditional interpolation algorithms, a new numerical control interpolation method—velocity interpolation, is presented in this paper. the realization steps of the quadratic curve in the numerical control system are described. through the analysis of the error caused by the error caused by the stepper motor in the stepper motor control system, a correction method is proposed to improve the machining accuracy. the simulation program is developed by VC++ to simulate the process of the quadratic curve, which is the representative of a parabola, and the feasibility of the modified method is verified.

关键词： velocity interpolation stepper motor VC++ quadratic curve

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A fast discrete small-world optimization algorithm

A fast discrete small-world optimization algorithm

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2015 5th international conference on Computer Sciences and Automation Engineering(ICCSAE 2015)

作者： Zhipeng Tian Haiping Zhu Xinyu Shao Huazhong University of Science & Technology

ISBN: (纸本)9781510818972

the application of complex networks in optimization field has received increasing attention recently. this paper proposes a discrete small-world optimization algorithm(DSWOA) based on the small-world network theory and Six Degrees of Separation principle in sociology. the DSWOA model is composed of a lot of short-range contacts and few long-range contacts. In this algorithm, the short-range contactsachieve the fast searching and the long-range contacts can accelerate the convergence rate. Next, extensive computational experiments are conducted to compare the DSWOA with other algorithms for the permutation flowshop scheduling problems(PFSP) by using the Taillard instances[1]. In the makespan tests, the results show that DSWOA has a stronger ability of quick searching, especially in the small-size problems. From the analysis results, the DSWOA has higher search efficiency than other algorithms.

关键词： Small-world network discrete small-world optimization permutation flowshop scheduling problem

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Human Action Recognition based on Convolutional Neural Networks with a Convolutional Auto-Encoder

Human Action Recognition based on Convolutional Neural Netwo...

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2015 5th international conference on Computer Sciences and Automation Engineering(ICCSAE 2015)

作者： Chi Geng JianXin Song Nanjing University of Post and Telecommunications

ISBN: (纸本)9781510818972

Human action recognition(HAR) research is hot in computer vision, but high precision recognition of human action in the complex background is still an open question. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs, which are driven by tasks and uncertain. In this paper, type of deep model convolutional neural network(CNN) is proposed for HAR that can act directly on the raw inputs. In addition, an efficient pre-training strategy has been introduced to reduce the high computational cost of kernel training to enable improved real-world applications. the proposed approach has been tested on the Kth database and the achieved results compares favorably against state-of-the-art algorithms using hand-designed features.

关键词： human action recognition Convolutional Neural Networks deep learning pre-training

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Poster: Classifying primary outcomes in rheumatoid arthritis: Knowledge discovery from clinical trial metadata

Poster: Classifying primary outcomes in rheumatoid arthritis...

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IEEE international conference on Computational Advances in Bio and Medical Sciences (ICCABS)

作者： Yuanyuan Feng Vandana P. Janeja Yelena Yesha Napthali Rishe Michael A. Grasso Amanda Niskar University of Maryland Baltimore County Baltimore USA Florida International University Florida USA University of Maryland School of Medicine Baltimore USA

Early prediction of treatment outcomes in RA clinical trials is critical for both patient safety and trial success. We hypothesize that an approach employing metadata of clinical trials could provide accurate classification of primary outcomes before trial implementation. We retrieved RA clinical trials metadata from ***. Four quantitative outcome measures that are frequently used in RA trials, i.e., ACR20, DAS28, and AE/SAE, were the classification targets in the model. Classification rules were applied to make the prediction and were evaluated. the results confirmed our hypothesis. We concluded that the metadata in clinical trials could be used to make early prediction of the study outcomes with acceptable accuracy.

关键词： Clinical trials Metadata Arthritis Diseases Predictive models Safety Classification algorithms

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A Review of High Dynamic Carrier Tracking algorithms Without External Aided Data

A Review of High Dynamic Carrier Tracking Algorithms Without...

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2015 5th international conference on Computer Sciences and Automation Engineering(ICCSAE 2015)

作者： Youmu Shi Di Yan Equipment Academy

the traditional PLL（Phase-locked loop） is used to track the GPS signal carrier. However, an unavoidable contradiction between the bandwidth of PLL and the measurement accuracy occurs when PLL works in a high dynamic situation. Consequently some solutions have been studied since 1980 s, which can be divided into two categories, namely with or without the aid of external data. the latter is always easy to realize and much cheaper. this thesis presents a review of the pure carrier tracking algorithms with no external aided data. And then examines various problems associated with these algorithms. Finally a corresponding comparison is made and a conclusion of these algorithms is given.

关键词： GPS high dynamic carrier tracking loop Kalman filter

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Multi Angle Analysis of the Existing Clustering algorithms

Multi Angle Analysis of The Existing Clustering Algorithms

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2015 5th international conference on Computer Sciences and Automation Engineering(ICCSAE 2015)

作者： Jinzhen Ping Qian Wang Lili Yu Xue Fang Wu Department of Software Engineering Shijiazhuang Information Engineering Vocational College

Data mining clustering is a broad research field. It is used to partition the data set of clusters. Different clustering methods use different similarity definition and technology. Several popular clustering algorithms are analyzed from three different perspectives: the clustering criterion, clustering algorithm and frame representation. Furthermore, some new construction algorithm, mixed or generalization of some algorithm were introduced. As a result of the analysis of several points of view, it can be covered and distinguished from most existing algorithms. It is based on self tuning algorithm and clustering benchmark.

关键词： data mining clustering algorithm

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the societal acceptance of private electro mobility in Germany and its perception by consumers: An empirical analysis of the status quo and the medium-term future expectations

The societal acceptance of private electro mobility in Germa...

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international Electric Drives Production conference (EDPC)

作者： Klaus Mühlbäck Tim Hendrikx Department of Strategic Marketing Management International School of Management Munich Germany

the combustion engine has a history of development for far more than 100 years. the last few decades has resulted in an increasing interest in electro mobility and can be described as a new technology era regarding road transport. Due to climate changes and the growing scarcity of energy resources, countries and cities are constantly trying to reduce CO2 emissions. Road transport is considered to be a large part of these emissions. the majority of vehicle manufacturers (such as BMW, Volkswagen and Renault) as well as new entrants such as Tesla are developing and realizing EVs with high speed. the following study recaptures the acceptance of private electro mobility in Germany. Potential users associate EVs with driving pleasure and fun. On the other hand, top speed is not considered to be a critical argument for purchasing an EV. Nowadays users place increasing importance on environmentally friendliness (which can be described as a “lifestyle" nowadays) and cost efficiency. the typical EV customer is considered to be technique affine with a modern lifestyle. these users are ready to pay a higher purchasing price for an EV, however are not yet willing to pay the current market prices which are demanded. Furthermore, the research summarizes the disadvantages of EVs which affect the consumer demand, such as the current charging infrastructure which is perceived as not fully developed yet. Additionally, individuals criticized security standards of EVs, as long term tests have not been conducted sufficiently, especially regarding the liability of both the electric engine and lithium-ion batteries. It is of great importance for EV manufacturers to work on improving the range and the purchasing cost. Concluding, the overall willingness of purchasing an EV in the future as well as to date is considered to be high. However, in the foreseeable future, the internal combustion engine will keep its importance.

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