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检索条件"主题词=detection algorithms"

共 7359 条记录，以下是91-100 订阅

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The Effect of Network Realism on Community detection algorithms

The Effect of Network Realism on Community Detection Algorit...

引用

International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Günce K. Orman Vincent Labatut Computer Science Department Galatasaray University Istanbul Turkey

Community detection consists in searching cohesive subgroups in complex networks. It has recently become one of the domain pivotal questions for scientists in many different fields where networks are used as modeling tools. algorithms performing community detection are usually tested on real, but also on artificial networks, the former being costly and difficult to obtain. In this context, being able to generate networks with realistic properties is crucial for the reliability of the tests. Recently, Lancichinetti et al. designed a method to produce realistic networks, with a community structure and power law distributed degrees and community sizes. However, other realistic properties such as degree correlation and transitivity are missing. In this work, we propose a modification of their approach, based on the preferential attachment model, in order to remedy this limitation. We analyze the properties of the generated networks and compare them to the original approach. We then apply different community detection algorithms and observe significant changes in their performances when compared to results on networks generated with the original approach.

关键词： Communities Barium Correlation detection algorithms Sensitivity Complex networks Algorithm design and analysis

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Performance evaluation of scene change detection algorithms

Performance evaluation of scene change detection algorithms

引用

Asia-Pacific Conference on Communications

作者： Jong Whan Jang Il Kyun Oh Department of Information and Communication Engineering Pai Chai University Taejon South Korea

ISBN: (纸本)7563504028

Scene change detection algorithms become the key issues especially for video information in many digital video applications such as digital libraries and video servers. The accuracy and execution speed of the scene change detection algorithm is critical if large amounts of video data are to be processed. In this paper, we discuss the performance of the three previous proposed methods and present a new algorithm to use the histogram difference of DC images incorporating the HVS (human visual system) for fast and accurate detection. The simulation results are also presented for two test video sequences, commercials and news, to show that the proposed algorithm works better than the previous ones.

关键词： Layout detection algorithms Video sequences Change detection algorithms Video on demand Video compression Information retrieval Histograms Decoding Computational efficiency

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Improving the Accuracy of Passive Duplicate Address detection algorithms over MANET On-demand Routing Protocols

Improving the Accuracy of Passive Duplicate Address Detectio...

引用

International Symposium on Autonomous Decentralized Systems (ISADAS)

作者： Dongkyun Kim Hong-Jong Jeong Sutaek Oh Juan-Carlos Cano Department of Computer Engineering Kyungpook National University Daegu Korea Department of Computer Engineering Polytechnic University of Valencia Spain

IP auto-configuration in mobile ad hoc networks has attracted much attention. Efficient DAD (duplicate address detection) techniques should be devised to provide each node with its unique address in the network. Generally, DAD schemes can be categorized into two classes: (a) active DAD and (b) passive DAD. In this paper, we focus on passive DAD schemes over on-demand ad-hoc routing protocols such as AODV and DYMO. In order to improve the accuracy of detecting address conflicts, we propose several schemes using additional information including sequence, location, or neighbor information

关键词： detection algorithms Mobile ad hoc networks Routing protocols Computer networks Manuals Performance analysis Mobile computing Portable computers Wireless networks Internet

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Shadow detection algorithms for traffic flow analysis: a comparative study

Shadow detection algorithms for traffic flow analysis: a com...

引用

International Conference on Intelligent Transportation

作者： A. Prati I. Mikic C. Grana M.M. Trivedi Dipartimento di Scienze Ingegneria Università di Modena e Reggio Emila Italy Department of Electrical and Computer Engineering University of California San Diego USA

Shadow detection is critical for robust and reliable vision-based systems for traffic flow analysis. In this paper we discuss various shadow detection approaches and compare two critically. The goal of these algorithms is to prevent moving shadows being misclassified as moving objects (or parts of them), thus avoiding the merging of two or more objects into one and improving the accuracy of object localization. The environment considered is an outdoor highway scene with multiple lanes observed by a single fixed camera. The important features of shadow detection algorithms and the parameter set-up are analyzed and discussed. A critical evaluation of the results both in terms of accuracy and in terms of computational complexity are outlined. Finally, possible integration of the two approaches into a robust shadow detector is presented as future direction of our research.

关键词： detection algorithms Algorithm design and analysis Robustness Merging Road transportation Layout Cameras Computer vision Computational complexity Detectors

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Distributed double threshold spatial detection algorithms in wireless sensor networks

Distributed double threshold spatial detection algorithms in...

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IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

作者： Stefania Sardellitti Sergio Barbarossa Luca Pezzolo INFOCOM Department University of Roma La Sapienza Rome Italy

In this paper we propose two alternative event-driven double threshold detection algorithms to be used in decentralized wireless sensor networks. The proposed approach assumes that a sensor may decide about the presence of an event of interest either directly or asking for additional data from nearby nodes. The proposed methods aim at minimizing the network energy consumption associated to the detection process. The problem is formulated associating a cost proportional to the (average) number of nodes involved in the decision. After a first activation phase, initiated by a single node, we examine two alternative approaches: a fixed sample size and a sequential detector. We show that there is a need of including an activation threshold when there is a stringent constraint on the power consumption or when the SNR on each sensor is quite low. We compare the performance of the proposed approaches showing that, also in this double threshold setup, sequential detection algorithms involve smaller average number of sensors to guarantee the same performance metrics.

关键词： detection algorithms Wireless sensor networks Energy consumption Measurement Frequency selective surfaces Signal to noise ratio Costs Event detection Testing Intelligent networks

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Performance Comparison of Rock detection algorithms for Autonomous Planetary Geology

Performance Comparison of Rock Detection Algorithms for Auto...

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IEEE Conference on Aerospace

作者： David R. Thompson Rebecca Castano The Robotics Institute Carnegie Mellon University Pittsburgh PA USA Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

Detecting rocks in images is a valuable capability for autonomous planetary science. Rock detection facilitates selective data collection and return. It also assists with image analysis on Earth. This work reviews seven rock detection algorithms from the autonomous science literature. We evaluate each algorithm with respect to several autonomous geology applications. Tests show the algorithms' performance on Mars Exploration Rover imagery, terrestrial images from analog environments, and synthetic images from a Mars terrain simulator. This provides insight into the detectors' performance under different imaging conditions.

关键词： detection algorithms Geology Image edge detection Mars Detectors Testing Laboratories Shape Propulsion Robots

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A new resource for independent and blinded assessment of QRS detection algorithms

A new resource for independent and blinded assessment of QRS...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： D. Tsunami J. McNames M. Aboy M.S. Ellenby Biomedical Signal Processing Laboratory Electrical and Computer Engineering Portland State University Portland OR USA Complex Systems Laboratory Pediatrics Oregon Health and Sciences University Portland OR USA

We describe a new resource for developers of QRS detection algorithms that provides a standardized assessment of algorithm performance that is blinded, objective, independent, and reproducible. This overcomes the problems of using a single data set for both development and assessment that leads to favorably biased estimates of performance.

关键词： detection algorithms Databases Electrocardiography Signal processing algorithms Laboratories Medical diagnostic imaging Pediatrics Algorithm design and analysis Heart rate Tsunami

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Multiple model estimation for improving conflict detection algorithms

Multiple model estimation for improving conflict detection a...

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IEEE International Conference on Systems, Man and Cybernetics

作者： L.C. Yang Ji Hyun Yang E.M. Feron Massachusetts Institute of Technology USA

We present a framework for improving conflict detection algorithms using a hybrid control paradigm. This allows us to separate the problem into two parts: state/mode estimation and threat prediction. Since the dynamic equations for a conflict can change discretely depending on the situation, we propose the use of multiple model (MM) estimators to predict the situation and ultimately improve threat assessment. We provide an example using two different MM estimators for a rear-end collision warning system. The estimators can be used to determine the scenario mode as well as improve the state estimates

关键词： detection algorithms State estimation Vehicle dynamics Automobiles Predictive models Road accidents Aircraft Collision avoidance Differential equations Vehicles

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Evaluating and Comparing the IGraph Community detection algorithms

Evaluating and Comparing the IGraph Community Detection Algo...

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Brazilian Conference on Intelligent Systems (BRACIS)

作者： Fabiano Berardo de Sousa Liang Zhao Inst. of Math. & Comput. Sci. Universidade de Sao Paulo Sao Paulo SÃ£o Paulo BR School of Philosophy Sciences and Literatures University of São Paulo Ribeirão Preto SP Brazil

Complex networks became a very important tool in machine learning field, helping researchers to investigate and mine data. They can model real dynamic networks, aiding to unveil information's about the systems they model. Communities are notable groups that may exist in a complex network and the community detection problem is the focus of attention of many researchers. The igraph library implements a good set of community detection algorithms, allowing researchers to easily apply them to data mining tasks. But each algorithm uses a different approach, leading to different performances. In this paper, the community detection algorithms implemented in the igraph library are investigated and ranked according to their performances in a set of different scenarios. Results show walktrap and multi-level got the highest scores while leading eigenvector and spinglass got the lowest ones. These findings are an important contribution for aiding researchers to select or discard algorithms in their own experiments using igraph library.

关键词： Communities Mathematical model Libraries Equations Graphics Algorithm design and analysis detection algorithms

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Acceleration of pedestrian detection algorithms on a multi-core vehicle computing platform

Acceleration of pedestrian detection algorithms on a multi-c...

引用

IEEE Youth Conference on Information, Computing and Telecommunication, YC-ICT

作者： Yongpan Liu Yihao Zhu Sunny Zhang Senjie Zhang Huazhong Yang TNList EE Department Tsinghua University Beijing China INTEL Research Laboratory Beijing China

Vehicle-based pedestrian detection system receives more and more attentions in road safety applications of the modern intelligent transportation system. However, the existed detection algorithms are too computing extensive for single core vehicle-based processors. As the promising multi-core architecture provides both energy efficient and powerful computing solutions, it is relevant to evaluate the up-to-date pedestrian detection algorithm on such novel platforms. This paper implemented a popular template based pedestrian detection algorithm on such platforms and gave out computing bottlenecks by profiling. Furthermore, we proposed an application aware multithread accelerating technique. Experimental results showed that our design can achieve nearly 2 - 4x speedups on multi-core processors for critical function blocks, which reduces total execution time ranging from 26 to 41%.

关键词： Acceleration detection algorithms Intelligent transportation systems Vehicle detection Road safety Intelligent vehicles Road transportation Computer architecture Energy efficiency Multicore processing

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