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Learning Using an Information fusion Approach 13

Learning Using an Information Fusion Approach

引用

13th International conference on Intelligent and Adaptive Systems and Software Engineering, IASSE 2004

作者： Rubin, Stuart Lee, Gordon K. SPAWAR Systems Center 53560 Hull Street San DiegoCA United States Dept. of Electrical & Computer Engineering San Diego State University 5500 Campanile Drive San DiegoCA92182-1326 United States

ISBN: (纸本)9781618398383

Learning algorithms generally rely on contemporary neural architectures having one or more hidden layers and they suffer from the same deficiencies that genetic algorithms and methodologies for non-trivial automatic programming do, namely, they cannot exploit inherent domain symmetries for the transference of knowledge from an application of lesser to greater rank, or across similar applications. As a direct consequence, no ensemble of contemporary neural architectures allows for the effective codification and transference of knowledge within a society of individuals (i.e., swarm knowledge). These deficiencies stem from the fact that contemporary neural architectures cannot reason symbolically using heuristic ontologies. They cannot, directly provide symbolic explanations of what was learned for purposes of inspection and verification. Moreover, they do not allow the knowledge engineer to precondition the internal feature space through the application of domain-specific modeling languages. A symbolic representation can support the heuristic evolution of an ensemble of neural architectures. Each neural network in the ensemble imbues a hidden layer and for this reason is NP-hard in its learning performance. It may be argued that the internal use of a neat representation subsumes the heuristic evolution of a scruffy one. It follows that there is a duality of representation under transformation. The goal of AI then is to find symbolic representations, transformations, and associated heuristic ontologies. This paper provides an introduction to this quest. © 2004. 13th International conference on Intelligent and Adaptive Systems and Software Engineering 2004, IASSE 2004. All rights reserved.

关键词： Ontology

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Multi-sensor, multi-source information fusion: architecture, algorithms, and applications - a panoramic overview

Multi-sensor, multi-source information fusion: architecture,...

引用

International conference on Computational Cybernetics (ICCC)

作者： B.V. Dasarathy Huntsville AL USA

This plenary presentation offers a panoramic overview of the field of multi-sensor, and/or multi-source information fusion from three complementary perspectives, namely, architectures, algorithms, and applications. This overview is developed through addressing the questions of 'what', 'why', 'when', and last but not least 'how' of information fusion and illustrating the answers with appropriate algorithmic and applicative examples

关键词： Feature extraction Iron Taxonomy Data processing Data mining Biosensors sensor fusion Security Bibliographies

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Airborne net-centric multi-INT sensor control, display, fusion, and exploitation systems

Airborne net-centric multi-INT sensor control, display, fusi...

引用

conference on Airborne Intelligence, Surveillance, Raconnaissance (ISR) Systems and applications

作者： von Berg, DCL Lee, JN Kruer, MR Duncan, MD Olchowski, FM Allman, E Howard, G USN Res Lab Div Opt Sci Washington DC 20375 USA

ISBN: (纸本)0819453323

The NRL Optical Sciences Division has initiated a multi-year effort to develop and demonstrate an airborne net-centric suite of multi-intelligence (multi-INT) sensors and exploitation systems for real-time target detection and targeting product dissemination. The goal of this Net-centric Multi-Intelligence fusion Targeting Initiative (NCMIFTI) is to develop an airborne real-time intelligence gathering and targeting system that can be used to detect concealed, camouflaged, and mobile targets. The multi-INT sensor suite will include high-resolution visible/infrared (EO/IR) dual-band cameras, hyperspectral imaging (HSI) sensors in the visible-to-near infrared, short-wave and long-wave infrared (VNIR/SWIR/LWIR) bands, Synthetic Aperture Radar (SAR), electronics intelligence sensors (ELINT), and off-board networked sensors. Other sensors are also being considered for inclusion in the suite to address unique target detection needs. Integrating a suite of multi-INT sensors on a single platform should optimize real-time fusion of the on-board sensor streams, thereby improving the detection probability and reducing the false alarms that occur in reconnaissance systems that use single-sensor types on separate platforms, or that use independent target detection algorithms on multiple sensors. In addition to the integration and fusion of the multi-INT sensors, the effort is establishing an open-systems net-centric architecture that will provide a modular "plug and play" capability for additional sensors and system components and provide distributed connectivity to multiple sites for remote system control and exploitation.

关键词： net-centric multi-INT intelligence surveillance reconnaissance fusion exploitation

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Novel visual sensor system fusing an active trinocular vision and a stereo vision for 3D range data acquisition

Novel visual sensor system fusing an active trinocular visio...

引用

conference on Machine Vision and Its Optomechatronic applications

作者： Kim, MY Cho, H Lee, HK Korea Adv Inst Sci & Technol Dept Mech Engn Taejon 305701 South Korea

ISBN: (纸本)0819455563

One of major research issues associated with 3D range acquisition is the creation of sensor systems with various functionalities and small size. A variety of machine vision techniques have been developed for the determination of 3D scene geometric information from 2D images. As one of active sensors, structured lighting method has been widely used because of its robustness on the illumination noise and its extractability of feature information of interest. As one of passive sensors, stereo vision does also due to its simple configuration and easy construction. In this work, we propose a novel visual sensor system for 3D range acquisition, using active technique and passive one simultaneously. The proposed sensor system includes inherently two types of sensors, an active trinocular vision and a passive stereo vision. In the active vision part of this sensor, the structured lighting method using multi-lasers is basically utilized. In its stereo vision part, a general passive stereo is constructed. Since each of them has its own advantages and disadvantages on the measurements of various objects, we propose sensor fusion algorithms for acquiring more reliable range information from them. To see how the proposed sensing system can be applied to real applications, we mount it on a mobile robot, and a series of experimental tests is performed for a variety of configurations of robot and environment. The sensing results are discussed in detail.

关键词： active trinocular sensor stereo vision 3D visual sensor sensor fusion

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Combined spectral and imaging IR sensor system for analysis of fires and retrieval of fire parameters

Combined spectral and imaging IR sensor system for analysis ...

引用

conference on Remote Sensing for Environmental Monitoring, GIS applications and Geology IV

作者： Kick, H Beier, K Lindermeir, E DLR German Aerosp Ctr Remot Sensing Technol Inst D-82234 Wessling Germany

ISBN: (纸本)0819455210

The infrared sensor system FASA (Fire Airborne Spectral Analyser) operated in a DLR research aircraft is a unique combination of an imager and a Fourier Transform Spectrometer used to detect, analyse and classify fires and volcanoes. In such cases, the scenes in the FTS field of view are generally inhomogeneous and not known a priori, and the data fusion approach of image and spectral data is supposed to overcome the difficulty hereby involved. The analysis of an artificial coal fire has provided us fundamental insights in how to model such fires and potential strategies for data evaluation. First and promising results will be presented. Moreover, the importance of aerosol contributions is examined and the feasibility to retrieve smoke particle parameters in the infrared is demonstrated.

关键词： spectral and imaging IR sensor system fire analysis retrieval algorithms

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fusion of multisensor remote sensing data for urban land cover classification

Fusion of multisensor remote sensing data for urban land cov...

引用

conference on Remote Sensing for Environmental Monitoring, GIS applications and Geology III

作者： Greiwe, A Bochow, M Ehlers, M Univ Vechta Res Ctr Geoinformat & Remote Sensing D-49364 Vechta Germany

ISBN: (纸本)0819451223

The motivation for data fusion is to reduce the limitations and uncertainties associated with single sensor data. In the context of remotely sensed data this is often performed by combining images of high spatial, resolution with those of high spectral resolution at different levels. In contrast to pixel-based approaches like Intensity-Hue-Saturation (IHS) or Principal Component (PC) we will focus on image fusion at feature level. The research of this paper was conducted within within the "HyScan" project which goal is to develop a GIS based analysis and mapping of surface characteristics in urban areas using hyperspectral images in combination with remote sensing data of very high spatial resolution. In most cases the classification of hyperspectral data is performed using methods like Spectral Angle Mapper (SAM) or Mixture Tuned Matched Filtering (MTMF). Reference spectra for those algorithms are stored in libraries which contain the spectra of pure materials so called endmembers. The problem is that endmembers that represent urban surface types often display a mixture of spectral pure materials and thus show flat spectra. As a result, those thematic endmembers can hardly be detected by standard algorithms like the Pixel Purity Index (PPI). As a consequence standard classification procedures fail. In order to improve the quality of results, we fuse hyperspectral data recorded by the DAIS sensor with high spatial resolution imagery (e.g. HRSC) for a combined endmember selection, classification, and structural analysis. After segmentation of the high spatial resolution data, appropriate thematic classes are manually defined. The resulting segments are used to detect a set of pure pixels in the hyperspectral data which represent thematic endmembers. The segments resulting from the spatial high resolution data are processed using the endmember abundances of the hyperspectral data through a combined classification. Method and initial results of our fusion method are pr

关键词： hyperspectral remote sensing classification data fusion segmentation

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Discrete event modeling and simulation: V-Lab® application to wireless sensor networks

Discrete event modeling and simulation: V-Lab&reg applicatio...

引用

2004 IEEE International conference on Systems, Man and Cybernetics, SMC 2004

作者： Sridhar, Prasanna Jamshidi, Mo Department of Electrical Engineering University of New Mexico Albuquerque NM United States

The need for modeling and simulation (M&S) is seen in many diverse applications such as multi-agent systems, robotics, control systems, software engineering, complex adaptive systems, and homeland security. With the emerging applications of multi-agent systems, there is always a need for simulation to verify the results before the actual implementation. Multi-agent simulation provides a test bed for several soft computing algorithms like fuzzy logic, neural networks (NN), probabilistic reasoning (Stochastic Learning Automata, Reinforcement learning), and evolutionary algorithms (Genetic algorithms). fusion of soft computing methodology with existing simulation tools yields several advantages in simulating multi-agent systems. Such a fusion provides a novel and systematic way of handling time-dependent parameters in the simulation without altering the essential functionality and problem-solving capabilities of soft computing elements. The fusion here is the extension of the capabilities of simulation tools with intelligent tools from soft computing. This paper proposes a methodology for combining the agent-based architecture, discrete event system and the soft-computing methods in the simulation of multi-agent systems and defines a framework called Virtual Laboratory (V-Lab®) for realizing such multi-agent system simulations. Detailed experimental results obtained from simulation of robotics agents and wireless sensor network is also discussed.

关键词： Virtual reality

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Automated development of linguistic-fuzzy classifier membership functions and weights for use in disparate sensor integration visible and infrared Imaging sensor classification

Automated development of linguistic-fuzzy classifier members...

引用

conference on Multisensor, Multisource Information fusion

作者： Nelson, BN Birenzvige, A Geocenters Inc Newton MA 02459 USA

ISBN: (纸本)0819453579

In support of the Disparate sensor Integration (DSI) Program a number of imaging sensors were fielded to determine the feasibility of using information from these systems to discriminate between chemical and conventional munitions. The camera systems recorded video from 160 training and 100 blind munitions detonation events. Two types of munitions were used;155 mm conventional rounds and 155 mm chemical simulant rounds. In addition two different modes of detonation were used with these two classes of munitions;detonation on impact (point detonation) and detonation in the air (airblasts). The cameras fielded included two visible wavelength cameras, a near infrared camera (peak responsivity of approximately 1 mum), a mid wavelength infrared camera system (3 mum to 5 mum) and a long wavelength infrared camera system (7.5 mum to 13 mum). Our recent work has involved developing Linguistic-Fuzzy Classifiers for performing munitions detonation classification with the DSI visible and infrared imaging sensors data sets. In this initial work, the classifiers were heuristically developed based on analyses of the training data features distributions. In these initial classification systems both the membership functions and the feature weights were hand developed and tuned. We have recently developed new methodologies to automatically generate membership functions and weights in Linguistic-Fuzzy Classifiers. This paper will describe this new methodology and provide an example of its efficacy for separating munitions detonation events into either air or point detonation. This is a critical initial step in achieving the overall goal of DSI;the classification of detonation events as either chemical or conventional. Further, the detonation mode is important as it significantly effects the dispersion of agents. The results presented in this paper clearly demonstrate that the automatically developed classifiers perform as well in this classification task as the previously developed an

关键词： feature level fusion explosives event classification spectral band fusion image processing

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Multi-resolution image data fusion using 2-D discrete wavelet transform and self-organizing neural networks

Multi-resolution image data fusion using 2-D discrete wavele...

引用

Proceedings VRCAI 2004 - ACM SIGGRAPH International conference on Virtual Reality Continuum and its applications in Industry

作者： Zhang, Q.P. Liang, M. Sun, W.C. Dept. of Computer Science Fudan University Shanghai 200433 China

ISBN: (纸本)1581138849

In recent years, many solutions to multi-resolution image data fusion have been proposed;however, it is difficult to simulate the human ability of image fusion when algorithms of image processing are piled up merely. On the basis of the review of researches on psychophysics and physiology of human vision, this paper presents an effective multi-resolution image data fusion methodology, which is based on discrete wavelet transform theory and self-organizing neural network, to simulate the processes of images recognition and understanding implemented in the human vision system. Through the two-dimensional wavelet transform, original images can be decomposed in to different types of details and levels. The integration rule can be built using self-organizing neural networks, just like the automatic work in human brain. As an example, the model is applied to images obtained by Cyclone Center Locating Satellite System (CCLSS). The effectiveness of the proposed model is demonstrated via results comparison with several other image fusion methods.

关键词： sensor data fusion

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fusion of vision, 3D gyro and GPS for camera dynamic registration

Fusion of vision, 3D gyro and GPS for camera dynamic registr...

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17th International conference on Pattern Recognition (ICPR)

作者： Hu, ZC Keiichi, U Lu, HQ Lamosa, F Kumamoto Univ Dept Comp Sci Kumamoto Japan

ISBN: (纸本)0769521282

This paper presents a novel framework of hybrid camera pose tracking system for outdoor navigation system. Traditional vision based or inertial sensor based solutions are mostly designed for well-structured environment, which is however unavailable for most outdoor uncontrolled applications. Our system combines vision, GPS and 3D inertial gyroscope sensors to obtain accurate and robust camera pose estimation result. The fusion approach is based on our PMM (parameterized model matching) algorithm, in which the road shape model is derived from the digital map referring to GPS absolute road position, and matches with road features extracted from the real image. Inertial data estimates the initial state of searching parameters, and also serves as relative tolerance to stable the pose output. The algorithms proposed in this paper are validated with the experimental results of real road tests under different road conditions.

关键词： Cameras

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