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检索条件"主题词=Pursuit algorithms"

共 488 条记录，以下是61-70 订阅

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L1 regularized projection pursuit for additive model learning

L1 regularized projection pursuit for additive model learnin...

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Xiao Zhang Lin Liang Xiaoou Tang Heung-Yeung Shum Center for Advanced Study Tsinghua University Beijing China Microsoft Research Asia Beijing China Microsoft Corporation Redmond Washington D.C. DC USA

In this paper, we present a L 1 regularized projection pursuit algorithm for additive model learning. Two new algorithms are developed for regression and classification respectively: sparse projection pursuit regression and sparse Jensen-Shannon Boosting. The introduced L 1 regularized projection pursuit encourages sparse solutions, thus our new algorithms are robust to overfitting and present better generalization ability especially in settings with many irrelevant input features and noisy data. To make the optimization with L 1 regularization more efficient, we develop an ldquoinformative feature firstrdquo sequential optimization algorithm. Extensive experiments demonstrate the effectiveness of our proposed approach.

关键词： pursuit algorithms Boosting Robustness Unsolicited electronic mail Additives Asia Neural networks Laplace equations Cost function

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Image screening based on projection pursuit for image recognition

Image screening based on projection pursuit for image recogn...

引用

International Conference on Pattern Recognition

作者： K. Arimura N. Hagita NTT Basic Research Laboratories Atsugi Kanagawa Japan

A new preprocessing method, called image screening, is presented for improving the recognition rate and efficiency in statistical image recognition. The problem of detecting a specified object in an input image is treated as a two-class classification problem in which the image falls into a set of subimages in the target object (figure) class and the other set of subimages in the ground class. An image screening algorithm selects a candidate set of subimages which are similar to the object class and rejects the remaining set using screening filters whose design is based on projection pursuit. The classifiers of the two classes are taken from the candidate set. Experimental results for eye and mouth detection in face images and text-area detection in document images demonstrate that this method improves the recognition rate and efficiency.

关键词： Image recognition Object detection pursuit algorithms Mouth Face detection Filters Algorithm design and analysis Throughput Principal component analysis Laboratories

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Tree structured pursuit for simultaneous image approximation

Tree structured pursuit for simultaneous image approximation

引用

Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Ariel J. Bernal Sebastian E. Ferrando Department of Electrical Engineering Ryerson University Toronto ONT Canada Department of Mathematics Ryerson University Toronto ONT Canada

The paper introduces an adapted orthonormal system to approximate a collection of given images. The associated construction is performed by a pursuit algorithm constrained to build a tree; the pursuit maximization is performed over a large dictionary of Haar wavelet-like functions. The approximations are given by vector valued discrete martingales that converge to the vector of input images. A natural application for our construction is the case when the set of images is given by a sequence of video frames. We describe the trade off between the size of the input set and the quality of the approximation and provide examples and comparisons.

关键词： Image coding Partitioning algorithms Image storage Costs pursuit algorithms Video compression Random variables Dictionaries Image converters Approximation algorithms

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Using generalized Choquet integral in projection pursuit based classification

Using generalized Choquet integral in projection pursuit bas...

引用

Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： Kebin Wu Zhenyuan Wang Pheng-Ann Heng Kwong-Sak Leung Dept. of Comput. Sci. & Eng. Chinese Univ. of Hong Kong Shatin China Dept. of Mathematical Sciences University of Texas at EI Paso EI Paso TX USA Dept. of Computer Science & Engineering The Chinese University of Hong Kong Shatin Hong Kong

ISBN: (纸本)0780370783

A generalized Choquet integral with respect to a nonadditive sign measure is proposed, and serves as an aggregation tool to project the points of feature space onto a real axis to reduce an n-dimensional classification problem into a one-dimensional classification problem. The learning procedure of this new classification algorithm, GCIPP (Generalized Choquet Integral based Projection pursuit), is just pursuing an appropriate projection direction optimally according to a criterion of minimizing the global misclassification rate. Such a nonlinear projection is characterized by the nonadditive sign measure and two weight vectors. The nonadditive sign measure is a proper representation of the contribution rate of each combination of the feature attributes, including each singleton, toward the classification, and its nonadditivity reflects the interactions among the feature attributes. Optimizing the sign measures and the weights is realized by an adaptive genetic algorithm. This new classifier is successfully tested on some simulated training data generated from the preset sign measures and weights, and it also performs well on several real-world data sets.

关键词： Classification algorithms Weight measurement Genetic algorithms Computer science pursuit algorithms Extraterrestrial measurements Testing Training data Performance evaluation Data mining

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A pursuit game with range-only measurements

A pursuit game with range-only measurements

引用

IEEE Conference on Decision and Control

作者： Shaunak D. Bopardikar Francesco Bullo Joao P. Hespanha Center for Control Dynamical Systems and Computation(CCDC) University of California슠Santa Barbara Santa Barbara CA USA

We address a discrete-time, pursuit-evasion game with alternate moves played between two kinds of players: the pursuer and the evader. The pursuer wishes to capture the evader while the evader¿s goal is to avoid capture. By capture, we mean that the distance between the players is no greater than 1 unit. We assume simple, first-order motion kinematics for the players. The pursuer can move with a step size of at most 1 unit while the evader can move with a maximum step size of ß ¿ 1 units. The pursuer is able to measure only its distance from the evader, before and after the evader¿s move. We propose a capture strategy and first show that for the game played in ¿ 2 , if ß ¿ 0.5, then a single pursuer captures the evader in finite time. Next, we show that if the game is played in ¿ 3 and if ß ¿ 0.5, then with a modified strategy, two identical cooperative pursuers capture the evader in finite time. Finally, we shed light on the performance of the capture strategy in the case of ß ¿ [0.5, 1] and the case of sensing errors via simulations. We also present a simulation study of a version of this game with simultaneous moves.

关键词： Target tracking Kinematics Surveillance Surges pursuit algorithms Sufficient conditions Algorithm design and analysis Biological materials Collaborative work Biotechnology

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A fast two-stage algorithm for realizing matching pursuit

A fast two-stage algorithm for realizing matching pursuit

引用

IEEE International Conference on Image Processing

作者： Kin-pong Cheung Yuk-Hee Chan Center for Multimedia Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China

ISBN: (纸本)0780367251

Matching pursuit has proved to be one of the most efficient techniques in various signal coding techniques. However, its computation effort is so tremendous that it may not be affordable in some real-time applications. A two-stage filtering structure for realizing matching pursuit has recently proposed. This paper presents an efficient algorithm for the implementation of the structure. The issues of how to determine the elementary dictionary and approximate a given initial dictionary are also addressed. Simulation results show that the proposed algorithm can achieve a significant improvement in the complexity-distortion performance.

关键词： Matching pursuit algorithms pursuit algorithms Dictionaries Filtering Matched filters Video coding Iterative algorithms Signal processing Image coding Speech coding

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Sparsity Update Subspace pursuit Algorithm for Compressed Spectrum Sensing

Sparsity Update Subspace Pursuit Algorithm for Compressed Sp...

引用

IEEE Vehicular Technology Conference

作者： Li Chang Jen-Ming Wu Inst. of Communications Engineering/Dept. of Electrical Engineering National Tsing Hua University Hsinchu Taiwan

ISBN: (纸本)9781479980925

This paper presents an Sparsity Update Subspace pursuit (SUSP) algorithm for compressed sparse signal reconstruction with unknown sparsity. From practical point of view, the sparsity information is usually unavailable in many applications. In particular, the compressed spectrum sensing application is considered in this paper . The proposed SUSP algorithm begins with sparsity estimation and iteratively updates the sparsity based on the the residual value with subspace pursuit approach. A termination criterion is developed to facilitate the convergence of the sparse update iteration. Moreover, a tail biting rule is devised to refine the reconstruction. Consequently, the sparse signal is recovered and the reconstruction performance is improved. The recovery rate performance is numerically evaluated for both the known sparsity and the unknown sparsity cases. For each case, the recovery mean square errors are also presented for the noisy noisy environment. The results show that the resulting performance outperforms the popular methods using the maximum pursuit or the subspace pursuit based approaches.

关键词： Compressive sensing (CS) sparse signal recovery greedy algorithm sparsity estimation greedy algorithm Subspace Signal restoration pursuit algorithms termination criteria COMPRESSED Signal reconstruction

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Path Tracking using Vector pursuit Algorithm for Tracked Vehicles Driving on the Soft Cohesive Soil

Path Tracking using Vector Pursuit Algorithm for Tracked Veh...

引用

SICE Annual Conference

作者： Tae-kyeong Yeu Soung-jea Park Sup Hong Hyung-woo Kim Jong-su Choi Maritime & Ocean Engineering Research(MOERI) KORDI Daejeon South Korea

Generally, tracked vehicles are used in military, agricultural and recreational applications where terrain conditions are improper or unpredictable. Tracked vehicles are better than wheeled vehicles due to the larger contact area of tracks providing better floatation and traction at various ground conditions. In this paper, the path tracking method is proposed for tracked vehicle driving on the deep-sea soft cohesive soil. Firstly, to generate the vehicle's motion following the specified path, the vector pursuit algorithm is used. Next, to drive the vehicle as the generated motion, the control method based on the relation between the traction force and the track slip is proposed. Finally, to prove the performance of vector pursuit algorithm, the numerical simulation is done. Also, to directly induce the relation of traction force-slip, the draw-bar pull test is executed

关键词： pursuit algorithms Vehicle driving Soil Land vehicles Road vehicles Force control Motion control Tracking Numerical simulation Testing

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Multi-robot Cooperative pursuit Based on Association Rule Data Mining

Multi-robot Cooperative Pursuit Based on Association Rule Da...

引用

International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Jun Li Qi-shu Pan Bing-rong Hong Mao-hai Li Sch. of Comput. Sci. & Technol. Harbin Inst. of Technol. Harbin China

An approach of cooperative hunting for multiple mobile targets by multi-robot is presented, which divides the pursuiting process into forming the pursuiting groups and capturing the targets. The data sets of attribute relationship is built by consulting many factors about capturing evaders, then the interesting rules can be found by data mining from the data sets to build the pursuiting groups. Through doping out the positions of targets, the members of pursuiting can confirm their destinations. Based on these extensions, a kind of multi-robot cooperative pursuit algorithm that allows dynamic alliance is proposed. The simulation results show that the mobile evaders can be captured effectively and efficiently, and prove the feasibility and validity of the given algorithm under dynamic environment.

关键词： Association rules Data mining Multiagent systems Fuzzy systems Computer science Mobile computing Doping pursuit algorithms Heuristic algorithms Shape

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A complete pursuit-evasion algorithm for two pursuers using beam detection

A complete pursuit-evasion algorithm for two pursuers using ...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： B.H. Simov S.M. LaValle G. Slutzki Enterprise Systems Technology Lab Hewlett Packard Company USA Department of Computer Science University of Illinois Urbana-Champaign IL USA Department of Computer Science Iowa State University Ames IA USA

We present an algorithm for a pair of pursuers, each with one rotating beam (flashlight, laser or a camera), searching for an unpredictable, moving target in a 2D environment (simple polygon). Given a polygon with n edges, the algorithm decides in time O(n/sup 4/) whether it can be cleared by the pursuers, and if so, constructs a search schedule. The pursuers are allowed to move on. the boundary and in the interior of the polygon. They are not required to maintain mutual visibility throughout the pursuit.

关键词： pursuit algorithms Robots Laser beams Cameras Military computing Sonar detection Polynomials Scheduling algorithm Processor scheduling Computational geometry

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