检索结果-内蒙古大学图书馆

IVVI 2.0: An intelligent vehicle based on computational perception

EXPERT SYSTEMS WITH applications 2014年第17期41卷 7927-7944页

作者： Martin, D. Garcia, F. Musleh, B. Olmeda, D. Pelaez, G. Marin, P. Ponz, A. Rodriguez, C. Al-Kaff, A. de la Escalera, A. Armingol, J. M. Univ Carlos III Madrid Intelligent Syst Lab Leganes Spain

This paper presents the IVVI 2.0 a smart research platform to foster intelligent systems in vehicles. Computational perception in intelligent transportation systems applications has advantages, such as huge data from vehicle environment, among others, so computer vision systems and laser scanners are the main devices that accomplish this task. Both have been integrated in our intelligent vehicle to develop cutting-edge applications to cope with perception difficulties, data processing algorithms, expert knowledge, and decision-making. The long-term in-vehicle applications, that are presented in this paper, outperform the most significant and fundamental technical limitations, such as, robustness in the face of changing environmental conditions. Our intelligent vehicle operates outdoors with pedestrians and others vehicles, and outperforms illumination variation, i.e.: shadows, low lighting conditions, night vision, among others. So, our applications ensure the suitable robustness and safety in case of a large variety of lighting conditions and complex perception tasks. Some of these complex tasks are overcome by the improvement of other devices, such as, inertial measurement units or differential global positioning systems, or perception architectures that accomplish sensor fusion processes in an efficient and safe manner. Both extra devices and architectures enhance the accuracy of computational perception and outreach the properties of each device separately. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Intelligent transportation systems Computer vision IR detection Data fusion Vehicle positioning

来源：评论

学校读者我要写书评

暂无评论

Robust and computationally efficient diffusion-based classification in distributed networks

Robust and computationally efficient diffusion-based classif...

引用

IEEE International conference on Acoustics, Speech and Signal Processing

作者： P. Binder M. Muma A. M. Zoubir Signal Process. Group Tech. Univ. Darmstadt Darmstadt Germany

ISBN: (纸本)9781467369985

Today's wireless sensor networks provide the possibility to monitor physical environments via small low-cost wireless devices. Given the large amount of sensed data, efficient and robust classification becomes a critical task in many applications. Typically, the devices must operate under stringent power and communication constraints and the transmission of observations to a fusion center (FC) is, in many cases, infeasible or undesired. A challenging research question in such cases is the design of data clustering and classification rules when each sensor collects a set of unlabelled observations that are drawn from a known number of classes. We propose two robust distributed hybrid classification algorithms, i.e., the Diffusion K-Medians and the Communicationally Efficient Distributed K-Medians. An extensive performance analysis in comparison to a benchmark algorithm is provided that investigates the error rates in dependence of different parameters of a distributed sensor network, and also considers communication cost. Our proposed algorithms, which are insensitive to outliers and various parameters, are applicable to on-line classification problems and scale well w.r.t. the number of classes.

关键词： K-medians diffusion distributed classification outlier robust outliers Robustness diffusion Error analysis data clustering Distribute DISTRIBUTED NETWORKS Communication Research sensor networks

来源：评论

学校读者我要写书评

暂无评论

Error diagnosis for energy efficient data aggregation in Wireless sensor networks

Error diagnosis for energy efficient data aggregation in Wir...

引用

International conference on (ISCO) Intelligent Systems and Control

作者： Chetan Ambekar Chirag Shinde Swapnil Betkar Aniket Indulkar K.J. Somaiya C.O.E. University of Mumbai Mumbai India A.C. Patil C.O.E University of Mumbai Mumbai India M.R.S.C.O.E University of Mumbai Mumbai India

sensor networks are collection of sensor nodes which co-operatively send sensed data to base station. As sensor nodes are battery driven, an efficient utilization of power is essential in order to use networks for long duration hence it is needed to reduce data traffic inside sensor networks, also reduced amount of data need to send to base station. The main goal of data aggregation algorithms is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced. Wireless sensor networks (WSN) offer an increasingly sensor nodes need less power for processing as compared to transmitting data. It is preferable to do in network processing inside network and reduce packet size. One such approach is data aggregation which attractive method of data gathering in distributed system architectures and dynamic access via wireless connectivity. Wireless sensor networks have limited computational power and limited memory and battery power, this leads to increased complexity for application developers and often results in applications that are closely coupled with network protocols. In this paper, a data aggregation framework along with the algorithm on wireless sensor networks is presented. The aim of the proposed work consist a detailed study regarding the error which can occur by the data aggregation and also the circuit complexity which is generated for reduction of these errors.

关键词： Temperature sensors Quality of service Artificial neural networks

来源：评论

学校读者我要写书评

暂无评论

Distributed Data fusion Algorithm for Wireless sensor Network

Distributed Data Fusion Algorithm for Wireless Sensor Networ...

引用

IEEE 11th International conference on Networking, Sensing and Control (ICNSC)

作者： Abdelgawad, A. Cent Michigan Univ Sch Engn & Technol Mt Pleasant MI 48859 USA

ISBN: (纸本)9781479931064

Signal processing in Wireless sensor Network (WSN) has a huge range of applications. Distributed Kalman Filter (DKF) is one of the most fundamental distributed estimation algorithms for scalable wireless sensor fusion. DKF finds applications in object tracking, environmental monitoring, surveillance, and many other applications. All algorithms proposed in the literature are based on static network. In reality, the network topology is changing. The topology change is often caused by node failure, which is due to energy depletion. In this work a DKF is proposed for such network. The simulation and the experimental results validate our proposed DKF. The experimental results show that each sensor node can run DKF with up to six neighbors.

关键词： Distributed Kalman Filter Digital Signal Processing Wireless sensor Network

来源：评论

学校读者我要写书评

暂无评论

Study of data fusion algorithms applied to unattended ground sensor network

Study of data fusion algorithms applied to unattended ground...

引用

conference on Signal Processing, sensor/Information fusion, and Target Recognition XXIII

作者： Pannetier, B. Moras, J. Dezert, J. Sella, G. Off Natl Etud & Rech Aerosp Informat Proc & Modelling Dept F-91761 Palaiseau France SAGEM Def & Opt Div CED CV F-91311 Massy France

ISBN: (纸本)9781628410280

In this paper, data obtained from wireless unattended ground sensor network are used for tracking multiple ground targets (vehicles, pedestrians and animals) moving on and off the road network. The goal of the study is to evaluate several data fusion algorithms to select the best approach to establish the tactical situational awareness. The ground sensor network is composed of heterogeneous sensors (optronic, radar, seismic, acoustic, magnetic sensors) and data fusion nodes. The fusion nodes are small hardware platforms placed on the surveillance area that communicate together. In order to satisfy operational needs and the limited communication bandwidth between the nodes, we study several data fusion algorithms to track and classify targets in real time. A multiple targets tracking (MTT) algorithm is integrated in each data fusion node taking into account embedded constraint. The choice of the MIT algorithm is motivated by the limit of the chosen technology. In the fusion nodes, the distributed MTT algorithm exploits the road network information in order to constrain the multiple dynamic models. Then, a variable structure interacting multiple model (VS-IMM) is adapted with the road network topology. This algorithm is well-known in centralized architecture, but it implies a modification of other data fusion algorithms to preserve the performances of the tracking under constraints. Based on such VS-IMM MIT algorithm, we adapt classical data fusion techniques to make it working in three architectures: centralized, distributed and hierarchical. The sensors measurements are considered asynchronous, but the fusion steps are synchronized on all sensors. Performances of data fusion algorithms are evaluated using simulated data and also validated on real data. The scenarios under analysis contain multiple targets with close and crossing trajectories involving data association uncertainties.

关键词： Multiple target tracking wireless sensor network data fusion architecture

来源：评论

学校读者我要写书评

暂无评论

Eliminating Mutual Views in fusion of Ranging and RGB-D Data From Robot Teams Operating in Confined Areas

Eliminating Mutual Views in Fusion of Ranging and RGB-D Data...

引用

conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Lyons, Damian M. Shrestha, Karma Fordham Univ Robot & Comp Vis Lab Bronx NY 10458 USA

ISBN: (纸本)9781628410587

We address the problem of fusing laser and RGB-Data from multiple robots operating in close proximity to one another. By having a team of robots working together, a large area can be scanned quickly, or a smaller area scanned in greater detail. However, a key aspect of this problem is the elimination of the spurious readings due to the robots operating in close proximity. While there is an extensive literature on the mapping and localization aspect of this problem, our problem differs from the dynamic map problem in that it involves at one kind of transient map feature, robots viewing other robots, and we know that we wish to completely eliminate all such mutual views. In prior work, we investigated the problem of fusing laser data from multiple robots in such a manner as to reject this spurious data from other robots. This work showed that a combination of local robot-based direction filtering and global map-based visibility filtering at a central map server removed 91% of the spurious data and resulted in a 98% quality improvement. In this paper we additionally consider the problem of fusing RGB-D data generated by a stereo-camera sensor. An approach based on a model of human visual attention is presented and compared with our prior work and with other related work. This approach is an order of magnitude faster than the prior work and yet rejects 73% of the spurious data producing a 55% quality improvement. Results are shown for this approach for two experiments with a two robot team operating in a confined indoor environment (4m x 4m).

关键词： cognitive robotics navigation sensory fusion

来源：评论

学校读者我要写书评

暂无评论

Drift Reduction in IMU-Only Pedestrian Navigation System in Unstructured Environment

Drift Reduction in IMU-Only Pedestrian Navigation System in ...

引用

Asian Control conference

作者： Muhammad Ilyas Kuk Cho Seung-Ho Baeg Sangdeok Park Intelligent Robot Engineering University of Science and Technology (UST) Robotics R&BD Group Korea Institute of Industrial Technology (KITECH)

ISBN: (纸本)9781479978632

This paper aims at developing algorithmic approach to reduce the error drift in navigation information using only single motion sensor i.e. inertial measurement unit (IMU) in an unstructured environment. The target application is pedestrian navigation system (PNS), but these algorithms are general for other applications too involving autonomous systems. A MEMS IMU is mounted on the foot of the agent in order to get benefit of known walking patterns of the wearer. algorithms are derived based on motion constraints of human walking and applied to reduce the inherent error drift in inertial navigation systems (INS). Experiments are conducted in indoor/outdoor unstructured environment to validate this algorithmic approach and shown that without using any other sensors and any other pre-conditions on the environment;we can reduce navigation errors significantly only by taking into account the motion constraints of human walking.

关键词： Pedestrian navigation system Inertial navigation Zero velocity update (ZUPT) Data fusion

来源：评论

学校读者我要写书评

暂无评论

On Distinguishing between Reliable and Unreliable sensors Without a Knowledge of the Ground Truth

On Distinguishing between Reliable and Unreliable Sensors Wi...

引用

IEEE WIC ACM International conference on Web Intelligence (WI)

作者： Anis Yazidi B. John Oommen Morten Goodwin Dept. of Computer Science University College of Oslo and Akershus Oslo Norway School of Computer Science Carleton University Ottawa Canada Dept. of ICT University of Agder Grimstad Norway

In many applications, data from different sensors are aggregated in order to obtain more reliable information about the process that the sensors are monitoring. However, the quality of the aggregated information is intricately dependent on the reliability of the individual sensors. In fact, unreliable sensors will tend to report erroneous values of the ground truth, and thus degrade the quality of the fused information. Finding strategies to identify unreliable sensors can assist in having a counter-effect on their respective detrimental influences on the fusion process, and this has has been a focal concern in the literature. The purpose of this paper is to propose a solution to an extremely pertinent problem, namely, that of identifying which sensors are unreliable without any knowledge of the ground truth. This fascinating paradox can be formulated in simple terms as trying to identify stochastic liars without any additional information about the truth. Though apparently impossible, we will show that it is feasible to solve the problem, a claim that is counter-intuitive in and of itself. To the best of our knowledge, this is the first reported solution to the aforementioned paradox. Legacy work and the reported literature have merely addressed assessing the reliability of a sensor by comparing its reading to the ground truth either in an online or an offline manner. The informed reader will observe that the so-called Weighted Majority Algorithm is a representative example of a large class of such legacy algorithms. The essence of our approach involves studying the agreement of each sensor with the rest of the sensors, and not comparing the reading of the individual sensors with the ground truth -- as advocated in the literature. Under some mild conditions on the reliability of the sensors, we can prove that we can, indeed, filter out the unreliable ones. Our approach leverages the power of the theory of Learning Automata (LA) so as to gradually learn the identity

关键词： sensor fusion sensor phenomena and characterization Learning automata Monitoring Reliability theory

来源：评论

学校读者我要写书评

暂无评论

Hybrid fusion and demosaicing algorithm with near-infrared image

Hybrid fusion and demosaicing algorithm with near-infrared i...

引用

conference on Multisensor, Multisource Information fusion - architectures, algorithms, and applications

作者： Luo, X. Y. Zhang, J. Dai, Q. H. Beihang Univ Image Proc Ctr Sch Astronaut Beijing 100191 Peoples R China Beihang Univ Sch Elect & Informat Engn Natl Key Lab CNS ATM Beijing 100191 Peoples R China Tsinghua Univ Tsinghua Natl Lab Informat Sci & Technol Dept Automat Beijing 100084 Peoples R China

ISBN: (纸本)9781628410587

In this paper, we propose a unified framework for color filter array (CFA) interpolation and visible/NIR image combination. The proposed method aims to reconstruct a high quality image from raw CFA data and the corresponding NIR image, similar to a multi-spectral fusion of color and NIR images. Based on NIR image, we impose a sparse constraint of gradient difference to modify the traditional color interpolation. The experiments indicate the effectiveness of our hybrid scheme to acquire joint color and NIR information in real-time, and show that this hybrid process can generate a better color image when compared with treating interpolation and fusion separately.

关键词： Color filter array demosaicing hybrid interpolation image fusion

来源：评论

学校读者我要写书评

暂无评论

Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2014

Multisensor, Multisource Information Fusion: Architectures, ...

引用

Multisensor, Multisource Information fusion: architectures, algorithms, and applications 2014

ISBN: (纸本)9781628410587

The proceedings contain 22 papers. The topics discussed include: embedding the results of focused Bayesian fusion into a global context;new results in semi-supervised learning using adaptive classifier fusion;probabilistic multi-source multi-INT Intel fusion benefit analysis;multi-sensor fusion with non-optimal decision rules: the challenges of open world sensing;characterization of computer network events through simultaneous feature selection and clustering of intrusion alerts;a metamaterial-inspired combined inductive-capacitive sensor;synchronous radiation sensing and 3D urban mapping for improved source identification;on an efficient and effective intelligent transportation system (ITS) using field and simulation data;and detection of oil pollution along the pipeline routes in tropical ecosystem from multi-spectral data.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：