Conferences related to Kernel

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2016 IEEE International Conference on Image Processing (ICIP)

Signal processing, image processing, biomedical imaging, multimedia, video, multidemensional.


IGARSS 2015 - 2015 IEEE International Geoscience and Remote Sensing Symposium

The Geoscience and Remote Sensing Society (GRSS) seeks to advance science and technology in geoscience, remote sensing and related fields using conferences, education and other resources. Its fields of interest are the theory, concepts and techniques of science and engineering as they apply to the remote sensing of the earth, oceans, atmosphere, and space, as well as the processing, interpretation and dissemination of this information.

  • IGARSS 2014 - 2014 IEEE International Geoscience and Remote Sensing Symposium

    GRSS seeks to advance science and technology in geoscience, remote sensing and related fields. IGARSS begins with a plenary session and tutorials on the most up-to-date topics. Paper, panel and poster sessions will be scheduled. The exhibit hall features the latest in geoscience instruments, equipment, software, publications, and scientific programs.

  • IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium

    GRSS seeks to advance science and technology in geoscience, remote sensing and related fields. IGARSS begins with a plenary session and tutorials on the most up-to-date topics. Paper, panel and poster sessions will be scheduled. The exhibit hall features the latest in geoscience instruments, equipment, software, publications, and scientific programs.

  • IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium

    Remote Sensing Techniques and Applications.

  • IGARSS 2011 - 2011 IEEE International Geoscience and Remote Sensing Symposium

    To gather world-class scientists, engineers and educators engaged in the fields of geoscience and remote sensing to meet and present their latest activities. Nearly 1900 participants from all over the world attended technical sessions, tutorials, exhibits and social activities at the 2010 event in Hawaii.

  • IGARSS 2010 - 2010 IEEE International Geoscience and Remote Sensing Symposium

    Remote Sensing techniques and applications


2013 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

Wavelet General Theory; Bases and Frames Theory; Filter Banks; Approximation Theory; Spline Theory; Time-Frequency Analysis; Integral Transforms; Visualization; Watermarking; Biometrics; Signal Estimation; Image Fusion; Image Recovery; Image Compression; Biomedical Imaging; Document Analysis; Learning Theory; Noise Reduction; Machine Vision; Classification; Feature Extraction; Emotion Computation; Cluster Analysis; Deformation Analysis; Descriptor of Shapes; Diagnosis of Faults; Intelligent Robot; Hand Gestures Classification; Image Indexing and Retrieval; Range Imaging and Detection; Seismological Signal Processing; Stochastic Pattern Recognition; Texture Analysis and Classification; Animation Image Analysis; Enhancement and Restoration; Handwritten and Printed Character Recognition; Analysis and Detection of Singularities; Artificial Life; Intelligent Control System; Intelligent Human Machine Interface; Information Safety

  • 2012 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

    Wavelet General Theory; Bases and Frames Theory; Filter Banks; Approximation Theory; Spline Theory; Time-Frequency Analysis; Integral Transforms; Visualization; Watermarking; Biometrics; Signal Estimation; Image Fusion; Image Recovery; Image Compression; Biomedical Imaging; Document Analysis; Learning Theory; Noise Reduction; Machine Vision; Classification; Feature Extraction; Emotion Computation; Cluster Analysis; Deformation Analysis; Descriptor of Shapes; Diagnosis of Faults; Intelligent Robot; Hand Gestures Classification; Image Indexing and Retrieval; Range Imaging and Detection; Seismological Signal Processing; Stochastic Pattern Recognition; Texture Analysis and Classification; Animation Image Analysis; Enhancement and Restoration; Handwritten and Printed Character Recognition; Analysis and Detection of Singularities; Artificial Life; Intelligent Control System; Intelligent Human Machine Interface; Information Safety.

  • 2011 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

    Wavelet General Theory; Bases and Frames Theory; Filter Banks; Approximation Theory; Spline Theory; Time-Frequency Analysis; Integral Transforms; Visualization; Watermarking; Biometrics; Signal Estimation; Image Fusion; Image Recovery; Image Compression; Biomedical Imaging; Document Analysis; Learning Theory; Noise Reduction; Machine Vision; Classification; Feature Extraction; Emotion Computation; Cluster Analysis; Deformation Analysis; Descriptor of Shapes; Diagnosis of Faults; Intelligent Robot.

  • 2010 International Conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

    Wavelet General Theory; Bases and Frames Theory; Filter Banks; Approximation Theory; Spline Theory; Time-Frequency Analysis; Integral Transforms; Visualization; Watermarking; Biometrics; Signal Estimation; Image Fusion; Image Recovery; Image Compression; Biomedical Imaging; Document Analysis; Learning Theory; Noise Reduction; Machine Vision; Classification; Feature Extraction; Emotion Computation; Cluster Analysis; Deformation Analysis; Descriptor of Shapes; Diagnosis of Faults; Intelligent Robot; Hand Gest


2013 International Joint Conference on Neural Networks (IJCNN 2013 - Dallas)

Neural Networks

  • 2012 International Joint Conference on Neural Networks (IJCNN 2012 - Brisbane)

    The annual IJCNN is the premier international conference in the field of neural networks.

  • 2011 International Joint Conference on Neural Networks (IJCNN 2011 - San Jose)

    IJCNN 2011 will include paper presentations, tutorials, workships, panels, special sessions and competitions on topics related to neural networks, including: Neural network theory and models; neural network applications; computational neuroscience; neurocognitive models; neuroengineering; neuroinformatics; neuroevolution; collective intelligence; embodied robotics; artificial life, etc.

  • 2010 International Joint Conference on Neural Networks (IJCNN 2010 - Barcelona)

  • 2009 International Joint Conference on Neural Networks (IJCNN 2009 - Atlanta)

    IJCNN is the premier international conference in the area of neural networks theory, analysis and applications. It is organized by the International Neural Networks Society (INNS) and sponsored jointly by INNS and the IEEE Computational Intelligence Society. This is an exemplary collaboration between the two leading societies on neural networks and it provides a solid foundation for the future extensive development of the field.

  • 2008 International Joint Conference on Neural Networks (IJCNN 2008 - Hong Kong)

    The IJCNN is the premier event in the field of neural networks. It covers all topics in neural network research (broadly defined).

  • 2007 International Joint Conference on Neural Networks (IJCNN 2007 - Orlando)

    The IJCNN is the premier event in the field of neural networks. It covers all topics in neural network research (broadly defined).


2012 International Conference on Digital Image Computing: Techniques and Applications (DICTA)

he International Conference on Digital Image Computing: Techniques and Applications (DICTA) is the main Australian Conference on computer vision, image processing, pattern recognition, and related areas. DICTA was established as a biannual conference in 1991 and became an annual event in 2007. It is the premiere conference of the Australian Pattern Recognition Society (APRS).

  • 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA)

    DICTA is the premiere conference of the Australian Pattern Recognition Society (APRS) focusing on Image Processing, Computer Vision, Pattern Recognition and related areas. It is a major outlet for published work in these fields and one of the main vehicles for engagement between the Australian research community and industry.

  • 2010 International Conference on Digital Image Computing: Techniques and Applications (DICTA)

    (DICTA) is the main Australian conference on machine vision, image processing, pattern recognition and related areas. Since its establishment, DICTA has been a biannual meeting. In 2008, it turned into an annual conference. It is the conference of the Australian Pattern Recognition Society (APRS).

  • 2009 Digital Image Computing: Techniques and Applications (DICTA)

    DICTA is the main Australian conference on digital image processing, machine vision and related areas. DICTA2009 will be the eleventh meeting hosted by Australian Pattern Recognition Society (APRS). This conference typically attracts 120 participants from Australia and the Asia Pacific regions as well as many international researchers.

  • 2007 Digital Image Computing Techniques and Applications DICTA

    DICTA is hosted by the Australian Pattern Recognition Society and is held in odd numbered years. DICTA typically attracts 150 participants including many international researchers. DICTA 2007 is the ninth meeting of this conference and comprise international keynote speakers, parallel sessions of contributed papers, and posters. The conference will be run as a DEST category E1 conference, including double peer review of full papers.


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Periodicals related to Kernel

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Image Processing, IEEE Transactions on

Signal-processing aspects of image processing, imaging systems, and image scanning, display, and printing. Includes theory, algorithms, and architectures for image coding, filtering, enhancement, restoration, segmentation, and motion estimation; image formation in tomography, radar, sonar, geophysics, astronomy, microscopy, and crystallography; image scanning, digital half-toning and display, andcolor reproduction.


Neural Networks, IEEE Transactions on

Devoted to the science and technology of neural networks, which disclose significant technical knowledge, exploratory developments, and applications of neural networks from biology to software to hardware. Emphasis is on artificial neural networks.


Signal Processing Letters, IEEE

Rapid dissemination of new results in signal processing world-wide.


Systems, Man, and Cybernetics, Part B, IEEE Transactions on

The scope of the IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or between machines, humans, and organizations. The scope of Part B includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, ...




Xplore Articles related to Kernel

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A higher-order Nyström scheme for electromagnetic scattering by arbitrarily shaped surfaces

Mei Song Tong; Weng Cho Chew IEEE Antennas and Wireless Propagation Letters, 2005

A higher-order Nystrom scheme is developed for electromagnetic scattering by arbitrary conducting scatterers. In our implementation, we employ a superparametric geometry mapping for arbitrary curvilinear surfaces to minimize the geometry error. The local correction for singular integral kernels is manipulated efficiently with the Lagrange interpolation of the unknown functions followed by singularity extraction and Duffy's transformation. Since this local correction ...


Enriched Trusted Platform and its Application on DRM

Yongdong Wu; Feng Bao 2008 Third Asia-Pacific Trusted Infrastructure Technologies Conference, 2008

The TCG (Trusted Computing Group) is an industry working group which aims to establish industry standards for trust and security in computing platforms. This paper enriches the TCG architecture by adding a SPM (Secure Process Manager) into the trusted platform as a kernel component for the purpose of process management. To attest a process/software to a remote peer, SPM will ...


Design Tradeoffs For Software-managed Tlbs

D. Nagle; R. Uhlig; T. Stanley; S. Sechrest; T. Mudge; R. Brown Proceedings of the 20th Annual International Symposium on Computer Architecture, 1993

First Page of the Article ![](/xploreAssets/images/absImages/00698543.png)


CLSIFT: An Optimization Study of the Scale Invariance Feature Transform on GPUs

Weiyan Wang; Yunquan Zhang; Long Guoping; Shengen Yan; Haipeng Jia 2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing, 2013

Scale Invariance Feature Transform (SIFT) is quite suitable for image matching because of its invariance to image scaling, rotation and slight changes in illumination or viewpoint. However, due to high computation complexity it's technically challenging to deploy SIFT in real time application situations. To address this problem, we propose CLSIFT, an OpenCL based highly speeded up and performance portable SIFT ...


New expressions of dyadic Green's functions in uniform waveguides with perfectly conducting walls

V. Daniele IEEE Transactions on Antennas and Propagation, 1982

New expressions of the dyadic Green's functions in uniform waveguides with perfectly conducting walls are obtained. Significant features of these expressions are an explicit modal evaluation of their singular part. The same forms as in the free space appear; moreover the use of the divergence theorem allow to apply thebigtriangledownoperator on the currents in the integral representations of the electromagnetic ...


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Educational Resources on Kernel

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eLearning

A higher-order Nyström scheme for electromagnetic scattering by arbitrarily shaped surfaces

Mei Song Tong; Weng Cho Chew IEEE Antennas and Wireless Propagation Letters, 2005

A higher-order Nystrom scheme is developed for electromagnetic scattering by arbitrary conducting scatterers. In our implementation, we employ a superparametric geometry mapping for arbitrary curvilinear surfaces to minimize the geometry error. The local correction for singular integral kernels is manipulated efficiently with the Lagrange interpolation of the unknown functions followed by singularity extraction and Duffy's transformation. Since this local correction ...


Enriched Trusted Platform and its Application on DRM

Yongdong Wu; Feng Bao 2008 Third Asia-Pacific Trusted Infrastructure Technologies Conference, 2008

The TCG (Trusted Computing Group) is an industry working group which aims to establish industry standards for trust and security in computing platforms. This paper enriches the TCG architecture by adding a SPM (Secure Process Manager) into the trusted platform as a kernel component for the purpose of process management. To attest a process/software to a remote peer, SPM will ...


Design Tradeoffs For Software-managed Tlbs

D. Nagle; R. Uhlig; T. Stanley; S. Sechrest; T. Mudge; R. Brown Proceedings of the 20th Annual International Symposium on Computer Architecture, 1993

First Page of the Article ![](/xploreAssets/images/absImages/00698543.png)


CLSIFT: An Optimization Study of the Scale Invariance Feature Transform on GPUs

Weiyan Wang; Yunquan Zhang; Long Guoping; Shengen Yan; Haipeng Jia 2013 IEEE 10th International Conference on High Performance Computing and Communications & 2013 IEEE International Conference on Embedded and Ubiquitous Computing, 2013

Scale Invariance Feature Transform (SIFT) is quite suitable for image matching because of its invariance to image scaling, rotation and slight changes in illumination or viewpoint. However, due to high computation complexity it's technically challenging to deploy SIFT in real time application situations. To address this problem, we propose CLSIFT, an OpenCL based highly speeded up and performance portable SIFT ...


New expressions of dyadic Green's functions in uniform waveguides with perfectly conducting walls

V. Daniele IEEE Transactions on Antennas and Propagation, 1982

New expressions of the dyadic Green's functions in uniform waveguides with perfectly conducting walls are obtained. Significant features of these expressions are an explicit modal evaluation of their singular part. The same forms as in the free space appear; moreover the use of the divergence theorem allow to apply thebigtriangledownoperator on the currents in the integral representations of the electromagnetic ...


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IEEE-USA E-Books

  • Monte Carlo Pose Estimation with Quaternion Kernels and the Bingham Distribution

    The success of personal service robotics hinges upon reliable manipulation of everyday household objects, such as dishes, bottles, containers, and furniture. In order to accurately manipulate such objects, robots need to know objects' full 6-DOF pose, which is made difficult by clutter and occlusions. Many household objects have regular structure that can be used to effectively guess object pose given an observation of just a small patch on the object. In this paper, we present a new method to model the spatial distribution of oriented local features on an object, which we use to infer object pose given small sets of observed local features. The orientation distribution for local features is given by a mixture of Binghams on the hypersphere of unit quaternions, while the local feature distribution for position given orientation is given by a locally-weighted (Quaternion kernel) likelihood. Experiments on 3D point cloud data of cluttered and uncluttered scenes generated from a structured light stereo image sensor validate our approach.

  • TimeFrequency and TimeScale Analysis

    This chapter contains sections titled: Time-Frequency Representations Spectrogram Wigner Distribution Kernel Method Time-Scale Representations Scalograms Summary References Recommended Exercises

  • Gene Selection for Microarray Data

    This chapter contains sections titled: Introduction, Review of Feature Selection Methods, The Potential Support Vector Machine for Feature Selection, The Gene Selection Protocol, Experiments, Summary, Appendix A: Derivation of the Dual Optimization Problem for the P-SVM, Appendix B: Measurements of Complex Features

  • GENERAL COMPUTER SECURITY ARCHITECTURE

    This chapter considers security capabilities within computing and communications devices. It considers the software that resides next to the hardware and controls the use of system resources by applications. The networking subsystem supported by the element software is responsible for the confidentiality and integrity of information transferred among elements, for the authentication of elements to one another, and for user authentication and access control in distributed systems. The chapter focuses on the element security software components, primarily for the kernel, security contexts, security-critical functions, and operating system (OS) implementations. OS implementations structured to use the common kernel interface to obtain basic services should be able to be closely controlled from an authorization perspective relatively easily since most hardware dependencies will be visible only in the kernel and the device drivers. Physical and administrative security mechanisms are the first lines of defense used to achieve security objectives.

  • Maximal Margin Perception

    This chapter contains sections titled: Introduction, Basic Approximation Steps, Basic Algorithms, Kernel Machine Extension, Soft Margin Extension, Experimental Results, Discussion, Conclusions, Appendix: Details of comparison against six other methods for iterative generation of support vector machines

  • Kernels on Structured Objects Through Nested Histograms

    We propose a family of kernels for structured objects which is based on the bag-ofcomponents paradigm. However, rather than decomposing each complex object into the single histogram of its components, we use for each object a family of nested histograms, where each histogram in this hierarchy describes the object seen from an increasingly granular perspective. We use this hierarchy of histograms to define elementary kernels which can detect coarse and fine similarities between the objects. We compute through an efficient averaging trick a mixture of such specific kernels, to propose a final kernel value which weights efficiently local and global matches. We propose experimental results on an image retrieval experiment which show that this mixture is an effective template procedure to be used with kernels on histograms

  • References

    Modern machine learning techniques are proving to be extremely valuable for the analysis of data in computational biology problems. One branch of machine learning, kernel methods, lends itself particularly well to the difficult aspects of biological data, which include high dimensionality (as in microarray measurements), representation as discrete and structured data (as in DNA or amino acid sequences), and the need to combine heterogeneous sources of information. This book provides a detailed overview of current research in kernel methods and their applications to computational biology.Following three introductory chapters -- an introduction to molecular and computational biology, a short review of kernel methods that focuses on intuitive concepts rather than technical details, and a detailed survey of recent applications of kernel methods in computational biology -- the book is divided into three sections that reflect three general trends in current research. The first part presents different ideas for the design of kernel functions specifically adapted to various biological data; the second part covers different approaches to learning from heterogeneous data; and the third part offers examples of successful applications of support vector machine methods.

  • List of Symbols

    Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifier--a limited, but well-established and comprehensively studied model--and extends its applicability to a wide range of nonlinear pattern-recognition tasks such as natural language processing, machine vision, and biological sequence analysis. This book provides the first comprehensive overview of both the theory and algorithms of kernel classifiers, including the most recent developments. It begins by describing the major algorithmic advances: kernel perceptron learning, kernel Fisher discriminants, support vector machines, relevance vector machines, Gaussian processes, and Bayes point machines. Then follows a detailed introduction to learning theory, including VC and PAC- Bayesian theory, data-dependent structural risk minimization, and compression bounds. Throughout, the book emphasizes the interaction between theory and algorithms: how learning algorithms work and why. The book includes many examples, complete pseudo code of the algorithms presented, and an extensive source code library.

  • A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities

    We devise and experiment with a dynamical kernel-based system for tracking hand movements from neural activity. The state of the system corresponds to the hand location, velocity, and acceleration, while the system's input are the instantaneous spike rates. The system's state dynamics is defined as a combination of a linear mapping from the previous estimated state and a kernel-based mapping tailored for modeling neural activities. In contrast to generative models, the activity-to-state mapping is learned using discriminative methods by minimizing a noise-robust loss function. We use this approach to predict hand trajectories on the basis of neural activity in the motor cortex of behaving monkeys and find that the proposed approach is more accurate than a static approach based on support vector regression and the Kalman filter.

  • COMPUTER SOFTWARE SECURITY

    This chapter considers security of applications, examining security threats to applications, and how to mitigate these threats. It first looks at the various aspects of security in any general-purpose unix and linux operating systems (OSs). The chapter then describes the role-based access control as implemented in the Solaris OS. Based on the protection ring model, Windows security components operate in two modes: the kernel mode (protection ring 0) and the user mode (protection ring 3). Next, the chapter focuses on the VXworks- and pSOS-type embedded OSs as these differ the most from the general-purpose OSs. It also shows how buffer overflows could be exploited in applications through stack and heap manipulations. Application software is a primary target and a major source of security problems. Finally, the chapter looks at anti-malware applications available for windows and unix-type OS.



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