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检索条件"主题词=Detection algorithms"

共 7324 条记录，以下是81-90 订阅

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Distributed double threshold spatial detection algorithms in wireless sensor networks

Distributed double threshold spatial detection algorithms in...

引用

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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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...

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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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Is Objective Function the Silver Bullet? A Case Study of Community detection algorithms on Social Networks

Is Objective Function the Silver Bullet? A Case Study of Com...

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

作者： Yang Yang Yizhou Sun Saurav Pandit Nitesh V. Chawla Jiawei Han Department of Computer Science & Engineering University of Notre Dame Notre Dame IN USA Department of Computer Science University of Illinois Urbana-Champaign Urbana IL USA

Community detection or cluster detection in networks is a well-studied, albeit hard, problem. Given the scale and complexity of modern day social networks, detecting ``reasonable'' communities is an even harder problem. Since the first use of k-means algorithm in 1960s, many community detection algorithms have been invented - most of which are developed with specific goals in mind and the idea of detecting ``meaningful'' communities varies widely from one algorithm to another. With the increasing number of community detection algorithms, there has been an advent of a number of evaluation measures and objective functions such as modularity and internal density. In this paper we divide methods of measurements in to two categories, according to whether they rely on ground-truth or not. Our work is aiming to answer whether these general used objective functions are well consistent with the real performance of community detection algorithms across a number of homogeneous and heterogeneous networks. Seven representative algorithms are compared under various performance metrics, and on various real world social networks.

关键词： Communities Social network services detection algorithms Measurement Clustering algorithms Benchmark testing Cities and towns

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FPGA Suitability for Implementation of Pedestrian detection algorithms for Autonomous Driving Application

FPGA Suitability for Implementation of Pedestrian Detection ...

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Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA), International Conference on

作者： Isha Gupta Deepti Prit Kaur Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (数字)9798350349221

ISBN: (纸本)9798350349238

An emerging field of study called autonomous driving seeks to create self-driving cars that can guarantee the safety of both passengers and other road users. Although several countries have already developed basic autonomous vehicles, more research is required for more sophisticated automation. Numerous different computer vision (CV) algorithms are needed to handle the extensive elements in an autonomous vehicle. Although many computer vision algorithms have already been built as software, they still require a stable hardware platform in order to be tested and used. Due to the many advantages it offers, Field Programmable Gate Array (FPGA) has become the most popular hardware platform. This paper addresses the significance and necessity of autonomous vehicles, highlighting one of their most difficult features— pedestrian detection. The paper also reviews the numerous advantages of FPGAs specifically for the development of autonomous driving challenging features like pedestrian detection and it also documents that how different researchers have used FPGA’s as their hardware platform to construct self-driving car’s features with an eye towards potential future improvements.

关键词： Computer vision Automation Pedestrians Software algorithms Feature extraction Hardware detection algorithms

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Efficient detection algorithms for Spatial Multiplexing Systems

Efficient Detection Algorithms for Spatial Multiplexing Syst...

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Wenjie Jiang Yusuke Asai Takeshi Onizawa Satoru Aikawa NTT Access Network Service Systems Laboratories NTT Corporation Yokosuka Kanagawa Japan

Recent studies indicate that spatial multiplexing (SM) systems have enormous potential for increasing the capacity of multiple input multiple output (MIMO) channels in rich scattering environments. In this paper, we present two efficient decision feedback equalization (DFE) algorithms for signal detection of SM scheme. The basic idea behind the new proposals is to reduce the complexity by separating the order search and filter generation. Compared with the conventional DFE detectors with optimal and suboptimal ordering rules, the new algorithms are less complex and achieve error performance that closely approximates that of the standard Bell Labs layered space time (BLAST) algorithm

关键词： detection algorithms Samarium Silicon carbide Decision feedback equalizers MIMO Detectors Scattering Filters Land mobile radio Mobile communication

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Evaluating Point-Cloud Based Safe Landing Zone detection algorithms for VTOL-UAV: An Overview

Evaluating Point-Cloud Based Safe Landing Zone Detection Alg...

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Conference on Digital Avionics Systems (DASC)

作者： Giridhar Vitta Bukka Peter Stütz Institute of Flight Systems University of the Bundeswehr Munich (UniBwM) Neubiberg Germany

ISBN: (数字)9798350349610

ISBN: (纸本)9798350349627

In scenarios of autonomous or semi-autonomous Vertical Takeoff and Landing based Un-manned Areal Vehicle deployment, the capacity to swiftly and accurately identify a viable Safe Landing Zone is paramount for the operational safety and efficacy of UAV missions. A Safe Landing Zone detection (SLZD) algorithm takes real-time perception data as input and outputs all the potential Safe Landing Zones that meet the criteria set by the hazard metrics. SLZD algorithms categorized based on their input data types are briefly discussed. Reasoning for choice of selecting LiDAR Point-Cloud based Safe Landing Zone detection (PC-SLZD) algorithms for the scope of this research paper is provided. The general structure of such PC-SLZ algorithm pipeline is provided. Sub-algorithms used to implement the components of this pipeline are listed. Potential main algorithms that are constructed by combining all promising sub-algorithms are proposed for further evaluation. The goal of this research paper is to provide an overview of PC-SLZD algorithms and propose a three-stage evaluation procedure. This procedure addresses four key requirements: robustness, accuracy, precision and computational efficiency, to facilitate selection of promising candidates in given applications.

关键词： Measurement Laser radar Pipelines Autonomous aerial vehicles Robustness Real-time systems Hazards Cognition Computational efficiency detection algorithms

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The Chase family of detection algorithms for multiple-input multiple-output channels

The Chase family of detection algorithms for multiple-input ...

引用

IEEE Conference and Exhibition on Global Telecommunications (GLOBECOM)

作者： D.W. Waters J.R. Barry School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

We introduce a new family of detectors for multiple-input multiple-output (MIMO) channels called Chase detectors because of their resemblance to the well-known Chase algorithm for soft decoding of error-control codes. A Chase detector is fully specified by only three simple parameters; nevertheless, it reduces to a wide range of previously reported MIMO detectors as special cases, including the maximum-likelihood and decision-feedback detectors. Based on the Chase framework, we propose two new detectors, the B-Chase and L-Chase detectors, both of which perform well on fading channels. In fact, the L-Chase detector is shown to outperform the BLAST-ordered decision-feedback detector by 9.8 dB, while simultaneously requiring 17% fewer computations, on a 4-input 4-output Rayleigh-fading channel with uncoded 4-QAM inputs. Under the same conditions, the B-Chase detector falls only 0.2 dB short of the minimum-mean-squared-error sphere detector, while requiring 50% fewer computations.

关键词： detection algorithms MIMO Detectors Decoding USA Councils Communications Society Performance analysis

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The non-linear characteristic of core function of RNS numbers and its effect on RNS to binary conversion and sign detection algorithms

The non-linear characteristic of core function of RNS number...

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： M. Abtahi P. Siy Department of Electrical and Computer Engineering Wayne State University Detroit MI USA

Residue number system (RNS) has been recognized as a robust method to perform computations in a parallel fashion. RNS operations provide us with the capability of solving a precise or fuzzy system using a low resolution multi-moduli system. Despite of the advantages of RNS operations in parallel addition, subtraction, and multiplication, it suffers from some drawbacks such as RNS to binary conversion, sign detection, parity detection, overflow detection, scaling and division by Burgess (1997), and Szaho and Tanaka (1967). Several techniques have been developed to alleviate these drawbacks. For instance MRC (mixed radix conversion) by Szaho and Tanaka (1967), New CRT II (Chinese residue theorem II) by Wang et al. (1998), and core function by Burgess (1997) and Gonella (1991) are some well-known techniques used for RNS to binary conversion. Our study is oriented upon core function. Core function has a non-linear characteristic that causes an ambiguity in RNS to binary conversion as well as sign detection algorithms. Our work is a discussion about the nonlinear characteristic of the core function and its effects on these algorithms. Also, we point to some solutions to alleviate or resolve any ambiguity due to this non-linearity.

关键词： detection algorithms Concurrent computing Cathode ray tubes Nonlinear equations Robustness Fuzzy systems Dynamic range

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The Effect of Network Realism on Community detection algorithms

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

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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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