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检索条件"主题词=Detection and tracking algorithms"

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ADAPTIVE LEARNING RATE FOR INCREASING LEARNING SPEED IN BACKPROPAGATION NETWORKS 2

ADAPTIVE LEARNING RATE FOR INCREASING LEARNING SPEED IN BACK...

引用

CONF ON SCIENCE OF ARTIFICIAL NEURAL NETWORKS 2

作者： JANAKIRAMAN, J HONAVAR, V Iowa State Univ. (United States)

ISBN: (纸本)0819412023

Backpropagation is a supervised learning algorithm for training multi-layer neural networks for function approximation and pattern classification by minimizing a suitably defined error metric (e.g., the mean square error between the desired and actual outputs of the network for a training set) using gradient descent. It does this by calculating the partial derivative of the overall error and changing each weight by a small amount (determined by the learning rate) in a direction that is expected to reduce the error. Despite its success on a number of real-world problems, backpropagation can be very slow (it requires hundreds of passes (epochs) through the training set). Also, its performance is extremely sensitive to the choice of parameters such as the learning rate. The mathematical considerations that go into the derivation of backpropagation require that the learning rate be as small as possible. On the other hand, in order reduce the number training epochs required to learn the desired input-output mapping, it is desirable to make the weight changes as large as possible without causing the error to increase. Also it is desirable to have an algorithm that can change the learning rate dynamically so that it is close to optimal (in terms of reducing the error as much as possible given the local gradient information) at each epoch (thereby eliminating the reliance on guesswork in the choice of the learning rate). Several authors have proposed methods for adaptively adjusting the learning rate based on certain assumptions about the shape of the error surface (e.g., quadratic) and/or estimation of higher order derivatives of the error with respect to the weights at a given point in the weight space. The primary disadvantage of such methods is that the estimation of second order derivatives is not only computationally expensive but also prone to inaccuracy due to the approximation of derivatives by discrete differences. In this paper we propose and evaluate a heuristic

关键词： Evolutionary algorithms Neural networks Iris Artificial neural networks Computer programming detection and tracking algorithms Network architectures Computer simulations Error analysis Machine learning

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FAULT detection EMPLOYING TRANSDUCER OPTIMISATION PROCEDURES 2

FAULT DETECTION EMPLOYING TRANSDUCER OPTIMISATION PROCEDURES

引用

2nd European Conference on Smart Structures and Materials

作者： WORDEN, K TOMLINSON, GR BURROWS, AP UNIV MANCHESTER DEPT ENGNDYNAM & CONTROL RES GRPMANCHESTER M13 9PLLANCSENGLAND

ISBN: (纸本)0819417009

This paper describes one possible way forward for smart structures in the domain of fault detection and classification using neural networks and genetic algorithms. Consideration is given to the incompatibility between numerical training data sets and real structures and how this may be ameliorated using optimization procedures for determining the number and location of transducers required to locate and classify a fault.

关键词： Sensors Transducers Neural networks Genetic algorithms Data modeling Diagnostics Smart materials Chemical elements detection and tracking algorithms Smart structures

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Contour detection using an improved Holistically-nested Edge detection network

Contour detection using an improved Holistically-nested Edge...

引用

Global Intelligent Industry Conference (GIIC)

作者： Xu, Zheng Luo, Haibo Hui, Bin Chang, Zheng Chinese Acad Sci Shenyang Inst Automat Shenyang 110016 Liaoning Peoples R China Univ Chinese Acad Sci Beijing 110049 Peoples R China Chinese Acad Sci Key Lab Optoelect Informat Proc Shenyang 110016 Liaoning Peoples R China Key Lab Image Understanding & Comp Vis Shenyang 110016 Liaoning Peoples R China

ISBN: (数字)9781510623002

ISBN: (纸本)9781510623002

Recently we have been concerned with locating and tracking targets in aerial videos. Targets in aerial videos usually have weak boundaries due to moving cameras. For the purpose of target detecting, detecting the contour of the target is needed and can help with improving the accuracy of target tracking. Edge detection has assisted in obtaining some advances in this effort. However, noisy images and weak boundary limit the performance of existing contour detecting algorithms. After analyzing the structures and edge maps of a Holistically-nested Edge detection network, we utilize the highest level side-output and improve the architecture of HED;firstly we cut and resized our images into 400*320 pixels. Secondly, we detected edges using our improved HED network. Finally, the contour of an object is found based on edge detecting in the previous stage. We have significantly decreased time spent by reducing 5 side output layers to only 1 and replacing the fusion layer with a refinement and image processing module which also helps with the result. The experimental results show that our algorithm outperforms the state-of-the-art regarding images with noise and weak boundary.

关键词： Edge detection Network architectures Target detection Video Cameras detection and tracking algorithms Convolution Convolutional neural networks

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Vertex tracking for grid-based motion compensation

Vertex tracking for grid-based motion compensation

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Conference on Digital Compression Technologies and Systems for Video Communications

作者： Schroder, K UNIV DORTMUND LEHRSTUHL NACHRICHTENTECHD-44221 DORTMUNDGERMANY

ISBN: (纸本)0819423564

To overcome some of the well-known artefacts stemming from block-based motion compensation, grid-based techniques have been proposed in the past as a promising alternative to block matching. While the latter is restricted to simple translational motion, grid-based compensation employs e.g. an affine model when triangular meshes are assumed. The theoretically superior model, however, will perform worse at object boundaries where the connectivity constraint of the meshes causes smoothing of the underlying discontinuous motion vector field. This effect can be diminished by providing an individual grid for each object in a scene. The crucial part of grid-based motion prediction is the technique of tracking mesh vertices. In contrast to block matching, motion estimation of vertices cannot be done independently without sacrificing prediction gain. This paper discuses different algorithms for vertex tracking. The issue of tracking at object boundaries and the influence of the resampling algorithm on the prediction gain are addressed in detail. Object grids, carrying both shape and motion information, are evaluated further in terms of shape coding efficiency and temporal scalability. Both aspects become important when aiming at functional coding for low bit rates, as it is currently being investigated in the framework of MPEG-4.

关键词： Stars detection and tracking algorithms Convolution Motion estimation Distortion Motion models Video Computer programming Volume rendering Fourier transforms

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Investigation of Training Sample Selection Methods for Object Classification in Sonar Imagery 22

Investigation of Training Sample Selection Methods for Objec...

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Conference on detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII

作者： Cook, Mattew Marchand, Bradley Naval Surface Warfare Ctr Panama City Div Dahlgren VA 22448 USA

ISBN: (数字)9781510608665

ISBN: (纸本)9781510608665

For Sonar Automatic Target Recognition problems, the number of mine-like objects is relatively small compared to the number non-mine-like objects available. This creates a heavy bias towards non-mine-like objects and increases the processing resources needed for classifier training. In order to reduce resource needs and the bias towards non-mine-like objects, we investigate selection methods for reducing the non-mine-like target samples while still maintaining as much of the original training information as possible. Specifically, we investigate methods for reducing sample size and bias while maintaining good classifier performance. Several methods are considered during this investigation that cover a wide range of techniques, including clustering and evolutionary algorithms. Each method is evaluated based on the classifier performance when trained on the chosen data samples and the execution time to select the new training set. Results on each method tested are presented using sonar data collected using a sidescan sonar system.

关键词： Target detection Evolutionary algorithms Automatic target recognition detection and tracking algorithms Image classification Image filtering Sensors Land mines Target recognition Warfare

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Model supported exploitation of aerial images

Model supported exploitation of aerial images

引用

1997 Conference on Visual Communications and Image Processing

作者： Chellappa, R UNIV MARYLAND CTR AUTOMAT RESCOLLEGE PKMD 20742

ISBN: (纸本)0819424358

Model-supported exploitation is a new paradigam in Image Understanding research. In this paradigm, three main technical areas have been identified: semi-automatic or automatic construction of site models, automated positioning of images to the sites, and monitoring of movable objects and construction activities. In this paper, we summarize recent progress in the detection and counting of vehicles in selected locales, monitoring and characterization of vehicle groupings. We present the algorithms used and the results obtained, The detection and counting method employs geometrical models and uses a spatial contour matching approach. The configuration detection method exploits knowledge of geometrical models in the frequency domain. The issues of parameter learning as well as sensitivity of the detection performance to misspecification of model and tuning parameters are briefly examined.

关键词： 3D modeling Data modeling Roads Sensors detection and tracking algorithms Fourier transforms Cameras Image processing Performance modeling Image understanding

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IU for military and intelligence applications, how automatic will it get?

IU for military and intelligence applications, how automatic...

引用

25th AIPR Workshop on Emerging Applications of Computer Vision

作者： Mundy, JL GE Corporate Research and Development Ctr. (United States)

ISBN: (纸本)0819423661

Over the last 30 years, there have been steady and reasonably extensive R&D activities applied to the problem of interpreting image data automatically. The goal of much of this research has been directed either at automatic target recognition (ATR) or at the automation of the functions of intelligence image analysis. These efforts have greatly advanced our understanding of the nature of image content and what is necessary to describe it using computer algorithms. On the other hand, the goal of automatic interpretation of complex scenes and the recognition of targets in the presence of clutter and occlusion is still not formalized at the level of an engineering discipline. This paper will review what the key issues are in achieving the automation of image understanding and provide examples of both success and still-unattainable interpretation capabilities.

关键词： Image analysis Automatic target recognition Inspection detection and tracking algorithms Sensors Image resolution Target recognition Image processing Image sensors Military intelligence

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Particle Filter for Long Range Radar in RUV

Particle Filter for Long Range Radar in RUV

引用

Conference on Signal and Data Processing of Small Targets

作者： Romeo, Kevin Willett, Peter Bar-Shalom, Yaakov Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

ISBN: (纸本)9781628410297

In this paper we present an approach for tracking with a high-bandwidth active radar in long range scenarios with 3-D measurements in r-u-v coordinates. The 3-D low-process-noise scenarios considered are much more difficult than the ones we have previously investigated where measurements were in 2-D (i.e., polar coordinates). We show that in these 3-D scenarios the extended Kalman filter and its variants are not desirable as they suffer from either major consistency problems or degraded range accuracy, and most flavors of particle filter suffer from a loss of diversity among particles after resampling. This leads to sample impoverishment and divergence of the filter. In the scenarios studied, this loss of diversity can be attributed to the very low process noise. However, a regularized particle filter is shown to avoid this diversity problem while producing consistent results. The regularization is accomplished using a modified version of the Epanechnikov kernel.

关键词： Particles Particle filters 3D metrology Radar Filtering (signal processing) Sensors Statistical analysis 3D acquisition detection and tracking algorithms Error analysis

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SEMIDIFFERENTIAL INVARIANTS - ALGEBRAIC-DIFFERENTIAL HYBRIDS

SEMIDIFFERENTIAL INVARIANTS - ALGEBRAIC-DIFFERENTIAL HYBRIDS

引用

3RD CONF ON HYBRID IMAGE AND SIGNAL PROCESSING

作者： KEMPENAERS, P VANGOOL, LJ OOSTERLINCK, A Catholic Univ. of Leuven (Belgium)

ISBN: (纸本)0819408670

In the realm of flexible automation, viewpoint independent object recognition will become increasingly important. An algorithm for the recognition of plane shapes under pseudo- perspective projection is presented. The method is based on the comparison of features that remain invariant under 2-D affine transformations. In particular, the work presented is part of the wider framework of semi-differential invariants. It was successfully tested on a database containing 42 objects.

关键词： Databases Image processing Affine motion model Signal processing Data modeling Image segmentation Object recognition detection and tracking algorithms Edge detection Algorithm development

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Phase retrieval of gratings by applying Fourier analysis

Phase retrieval of gratings by applying Fourier analysis

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19th Congress of the International-Commission-for-Optics

作者： Castaneda, R Garcia-Sucerquia, J Medina, FF Univ Nacl Colombia Medellin Dept Phys AA-3840 Medellin Colombia

The phase distribution of regular gratings can be determined by Fourier analysing the Fraunhofer interference pattern it produces under spatially coherent illumination.

ISBN: (纸本)0819445967

The phase distribution of regular gratings can be determined by Fourier analysing the Fraunhofer interference pattern it produces under spatially coherent illumination.

关键词： Phase retrieval Fourier transforms Physics detection and tracking algorithms Spatial coherence Superposition

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