IEEE Organizations related to Histograms

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Conferences related to Histograms

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2016 IEEE International Conference on Image Processing (ICIP)

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


2012 8th International Conference on Natural Computation (ICNC)

ICNC is an international forum on intelligent systems inspired from nature, particularly neural, biological, and nonlinear systems, with applications to signal processing, communications, biomedical engineering and more.

  • 2011 Seventh International Conference on Natural Computation (ICNC)

    ICNC is an international forum on intelligent systems inspired from nature, particularly neural, biological, and nonlinear systems, with applications to signal processing, communications, biomedical engineering, and more.

  • 2010 Sixth International Conference on Natural Computation (ICNC)

    ICNC is an international forum on intelligent systems inspired from nature, particularly neural, biological, and nonlinear systems, with applications to signal processing, communications, biomedical engineering, and more.



Periodicals related to Histograms

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Medical Imaging, IEEE Transactions on

Imaging methods applied to living organisms with emphasis on innovative approaches that use emerging technologies supported by rigorous physical and mathematical analysis and quantitative evaluation of performance.


Pattern Analysis and Machine Intelligence, IEEE Transactions on

Statistical and structural pattern recognition; image analysis; computational models of vision; computer vision systems; enhancement, restoration, segmentation, feature extraction, shape and texture analysis; applications of pattern analysis in medicine, industry, government, and the arts and sciences; artificial intelligence, knowledge representation, logical and probabilistic inference, learning, speech recognition, character and text recognition, syntactic and semantic processing, understanding natural language, expert systems, ...


Signal Processing Letters, IEEE

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


Visualization and Computer Graphics, IEEE Transactions on

Specific topics include, but are not limited to: a) visualization techniques and methodologies; b) visualization systems and software; c) volume visulaization; d) flow visualization; e) information visualization; f) multivariate visualization; g) modeling and surfaces; h) rendering techniques and methodologies; i) graphics systems and software; j) animation and simulation; k) user interfaces; l) virtual reality; m) visual programming and program visualization; ...



Most published Xplore authors for Histograms

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Xplore Articles related to Histograms

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A Novel Method for Video Shot Similarity Measures

Li Deng; Li-zuo Jin; Shu-min Fei 2006 International Conference on Machine Learning and Cybernetics, 2006

In this paper, a novel method is proposed to determine the similarity between video shots. A video shot is treated as an ensemble that consists of multiple video key frames, so the shot similarity can be measured by the ensemble similarity. Based on nonlinear mapping, the original space is mapped to a high dimension space where the ensemble distribution can ...


Comparative study of digital image enhancement approaches

Showkat Hassan Malik; Tariq Ahmad Lone 2014 International Conference on Computer Communication and Informatics, 2014

Image enhancement can effectively improve the perception of information from images. This paper provides a comparative study of enhancement approaches applied to digital images with special emphasis on medical images. The paper is organized as follows: Section I gives general introduction to image enhancement approaches along with their critical review. Section II gives a brief description of enhancement approaches. Section ...


Performance Improvement of Face Recognition System by Decomposition of Local Features Using Discrete Wavelet Transforms

Neelamma K. Patil; S. Vasudha; Lokesh R. Boregowda 2013 International Symposium on Electronic System Design, 2013

As one of the most sought after applications of image analysis, face recognition has received significant attention, especially during the past two decades. Automatic human face recognition has received substantial attention in the recent few years, from researchers in biometrics, pattern recognition and computer vision communities, owing to the high demand for advanced security and authentication needs. Although the existing ...


Testing of embedded A/D converters in mixed-signal circuit

N. Ben-Hamida; B. Ayari; B. Kaminska Proceedings International Conference on Computer Design. VLSI in Computers and Processors, 1996

In this paper, a complete functional testing of embedded ADC is presented. The integral non-linearity error, INLE, differential non-linearity error, DNLE, offset error, OSE, gain error and the signal-to-noise ratio, SNR are rested. The problem related to the propagation of the analog signal to the input of the ADC and the observation of the digital output of the converter at ...


A 3D Shape Descriptor Based on Depth Complexity and Thickness Histograms

Wagner Schmitt; Jose L. Sotomayor; Alexandru Telea; Cláudio T. Silva; João L. D. Comba 2015 28th SIBGRAPI Conference on Graphics, Patterns and Images, 2015

Geometric models play a vital role in several fields, from the entertainment industry to scientific applications. To reduce the high cost of model creation, reusing existing models is the solution of choice. Model reuse is supported by content-based shape retrieval (CBR) techniques that help finding the desired models in massive repositories, many publicly available on the Internet. Key to efficient ...


More Xplore Articles

Educational Resources on Histograms

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eLearning

A Novel Method for Video Shot Similarity Measures

Li Deng; Li-zuo Jin; Shu-min Fei 2006 International Conference on Machine Learning and Cybernetics, 2006

In this paper, a novel method is proposed to determine the similarity between video shots. A video shot is treated as an ensemble that consists of multiple video key frames, so the shot similarity can be measured by the ensemble similarity. Based on nonlinear mapping, the original space is mapped to a high dimension space where the ensemble distribution can ...


Comparative study of digital image enhancement approaches

Showkat Hassan Malik; Tariq Ahmad Lone 2014 International Conference on Computer Communication and Informatics, 2014

Image enhancement can effectively improve the perception of information from images. This paper provides a comparative study of enhancement approaches applied to digital images with special emphasis on medical images. The paper is organized as follows: Section I gives general introduction to image enhancement approaches along with their critical review. Section II gives a brief description of enhancement approaches. Section ...


Performance Improvement of Face Recognition System by Decomposition of Local Features Using Discrete Wavelet Transforms

Neelamma K. Patil; S. Vasudha; Lokesh R. Boregowda 2013 International Symposium on Electronic System Design, 2013

As one of the most sought after applications of image analysis, face recognition has received significant attention, especially during the past two decades. Automatic human face recognition has received substantial attention in the recent few years, from researchers in biometrics, pattern recognition and computer vision communities, owing to the high demand for advanced security and authentication needs. Although the existing ...


Testing of embedded A/D converters in mixed-signal circuit

N. Ben-Hamida; B. Ayari; B. Kaminska Proceedings International Conference on Computer Design. VLSI in Computers and Processors, 1996

In this paper, a complete functional testing of embedded ADC is presented. The integral non-linearity error, INLE, differential non-linearity error, DNLE, offset error, OSE, gain error and the signal-to-noise ratio, SNR are rested. The problem related to the propagation of the analog signal to the input of the ADC and the observation of the digital output of the converter at ...


A 3D Shape Descriptor Based on Depth Complexity and Thickness Histograms

Wagner Schmitt; Jose L. Sotomayor; Alexandru Telea; Cláudio T. Silva; João L. D. Comba 2015 28th SIBGRAPI Conference on Graphics, Patterns and Images, 2015

Geometric models play a vital role in several fields, from the entertainment industry to scientific applications. To reduce the high cost of model creation, reusing existing models is the solution of choice. Model reuse is supported by content-based shape retrieval (CBR) techniques that help finding the desired models in massive repositories, many publicly available on the Internet. Key to efficient ...


More eLearning Resources

IEEE-USA E-Books

  • Histogram Operations

    The implementation of histograms and histogram based processing are discussed in this chapter. Techniques of accumulating a histogram, and then extracting data from the histogram are described in detail. Histogram equalisation, threshold selection, and the use of clustering for colour segmentation and classification is also discussed. The chapter concludes with the use of features extracted from multidimensional histograms for texture analysis.

  • No title

    <p>Over the last decade, differential privacy (DP) has emerged as the de facto standard privacy notion for research in privacy-preserving data analysis and publishing. The DP notion offers strong privacy guarantee and has been applied to many data analysis tasks.</p><p>This Synthesis Lecture is the first of two volumes on differential privacy. This lecture differs from the existing books and surveys on differential privacy in that we take an approach balancing theory and practice. We focus on empirical accuracy performances of algorithms rather than asymptotic accuracy guarantees. At the same time, we try to explain why these algorithms have those empirical accuracy performances. We also take a balanced approach regarding the semantic meanings of differential privacy, explaining both its strong guarantees and its limitations.</p><p>We start by inspecting the definition and basic properties of DP, and the main primitives for achieving DP. Then, w give a detailed discussion on the the semantic privacy guarantee provided by DP and the caveats when applying DP. Next, we review the state of the art mechanisms for publishing histograms for low-dimensional datasets, mechanisms for conducting machine learning tasks such as classification, regression, and clustering, and mechanisms for publishing information to answer marginal queries for high-dimensional datasets. Finally, we explain the sparse vector technique, including the many errors that have been made in the literature using it.</p><p>The planned Volume 2 will cover usage of DP in other settings, including high-dimensional datasets, graph datasets, local setting, location privacy, and so on. We will also discuss various relaxations of DP.</p>

  • Inserting Illustrations into Reports

    Illustrations appear mostly in longer, more formal reports, such as analyses, feasibility studies, proposals, and investigation or evaluation reports. For selecting and designing the most effective illustration for a given situation, three issues need to be clarified: which the kind of illustration (tables, graphs, bar charts, histograms, surface charts, pie charts, flow charts, and photographs) can best illustrate the particular feature or characteristic for the readers to comprehend; whether the illustration is simply used by the readers to gain a visual impression of an aspect being discussed, or can it be used to extract information; and is the illustration referred to only once to explain a point, or is it referred to several times in the report. Computer software can be used, with care, for illustration preparation. This chapter describes various ways to present information graphically, and explains what type of information is best suited for each.

  • Histogram Analysis

    This chapter contains sections titled: Early Histogram Analysis Notation Additive Independent Noise Multi-dimensional Histograms Experiment and Comparison

  • Appendix D: Calculation of Shell Frequency Distribution

    This chapter includes the following topics: Partial Histograms Partial Histograms for General Cost Functions Frequencies of Shells

  • Histogram Processing

    This chapter contains sections titled: Image Histogram: Definition and Example Computing Image Histograms Interpreting Image Histograms Histogram Equalization Direct Histogram Specification Other Histogram Modification Techniques Tutorial 9.1: Image Histograms Tutorial 9.2: Histogram Equalization and Specification Tutorial 9.3: Other Histogram Modification Techniques Problems

  • Beyond 2001: The Linguistic Spatial Odyssey

    This chapter contains sections titled: Introduction Force Histograms and Linguistic Scene Description Scene Matching Human-Robot Dialog Sketched Route Map Understanding The Future This chapter contains sections titled: Acknowledgments References

  • Fast Discriminative Visual Codebooks using Randomized Clustering Forests

    Some of the most effective recent methods for content-based image classification work by extracting dense or sparse local image descriptors, quantizing them according to a coding rule such as k-means vector quantization, accumulating histograms of the resulting "visual word" codes over the image, and classifying these with a conventional classifier such as an SVM. Large numbers of descriptors and large codebooks are needed for good results and this becomes slow using k-means. We introduce Extremely Randomized Clustering Forests -- ensembles of randomly created clustering trees -- and show that these provide more accurate results, much faster training and testing and good resistance to background clutter in several state-of-the-art image classification tasks.

  • No title

    Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc. Initial research in outlier detection focused on time series- based outliers (in statistics). Since then, outlier detection has been studied on a large variety of data types including high-dimensional data, uncertain data, stream data, network data, time series data, spatial data, and spatio- temporal data. While there have been many tutorials and surveys for general outlier detection, we focus on outlier detection for temporal data in this book. A large number of applications generate temporal datasets. For example, in our everyday life, various kinds of records like credit, personnel, financial, judicial, medical, etc., are all temporal. This stresses the need for an organized and detailed study of outliers with respect to such temporal data. In the past decade, there has been a lot of research on various forms of temporal data including consecutive data snapshots, series of data snapshots and data streams. Besides the initial work on time series, researchers have focused on rich forms of data including multiple data streams, spatio-temporal data, network data, community distribution data, etc. Compared to general outlier detection, techniques for temporal outlier detection are very different. In this book, we will present an organized picture of both recent and past research in temporal outlier detection. We start with the basics and then ramp up the reader to the main ideas in state-of-the-art outlier detection techniques. We motivate the importance of temporal outlier detection and brief the challenges beyond usual outlier detection. Then, we list down a taxonomy of proposed techniques for temporal outlier detection. Such techniques broadly include statistical techniques (like AR models, Markov models, histograms, neura networks), distance- and density-based approaches, grouping-based approaches (clustering, community detection), network-based approaches, and spatio-temporal outlier detection approaches. We summarize by presenting a wide collection of applications where temporal outlier detection techniques have been applied to discover interesting outliers.

  • Generate Quality Graphs

    This chapter covers the most effective ways to display data in various graphical forms. It also showcases the kinds of visuals that engineers, scientists, and technical experts use daily. Identifying the typical design traps that ensnare even the most well-intentioned professionals can help us avoid creating junk and, instead, propel us toward elegance and simplicity. Whether the presenter is creating a plot, a chart, or a table, there are a few aspects of design that can ensure success for the visual. These basic tenets can save embarrassment and audience frustration if applied well during the planning process. Establishing a baseline of best practices for pie charts enables avoiding many of the typical mistakes that can happen with this simple chart type. Bar charts and histograms appear frequently in engineering, scientific, and technical presentations and papers because they provide visual comparison that the user can digest quickly and easily.



Standards related to Histograms

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No standards are currently tagged "Histograms"


Jobs related to Histograms

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