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Showing 1 to 20 of 246 for “"Histogram"”.
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Histogram sort with sampling
The student, - Vipul Harsh, submitted this Thesis for approval on 2017-07-04 at 08:53.
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A parallel multidimensional weighted histogram analysis method
The Weighted Histogram Analysis Method (WHAM) is a technique used to calculate free energy from molecular simulation data. WHAM recombines biased distributions of samples from multiple Umbrella Sampling simulations to yield an estimate of the global unbiased distribution. The WHAM algorithm …
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Comparative analysis of image search algorithm using average RGB, local color histogram, global color histogram and color moment HSV
… Blue Color Channels (Average RGB), Local Color Histogram (LCH), Global Color Histogram (GCH) and Color Moment of Hue, Saturation and Brightness Value (HSV) to retrieve relevant images based on colour. These techniques are applied on the collection of three images chosen randomly from each class …
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Aplikace pro demonstraci metody Histogram of Oriented Gradients pro detekci objektů
… práce je shrnutí teorie, ze které vychází metoda Histogram of oriented gradients a následné zpracování vlastního algoritmu pro demonstraci výpočtu a vizualizace vektorů příznakového deskriptoru HOG, natrénování algoritmu SVM a následná detekce objektu. Jako prostředí pro práci bylo zvoleno MS …
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Histogram equalization for robust text-independent speaker verification in telephone environments
Word processed copy. Includes bibliographical references.
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A New Breast Cancer Image Classifier Using Gaussian Mixture Model Based on Histogram and Enhanced Roughness Index
<p>Early stage breast cancer detection is a critical challenge to improve survive rate, and thus it is extremely important to perform breast tumor image classification. In this thesis, a new method based on Gaussian Mixture Model (GMM) to perform the breast tumor classification into two different …
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Using the Earth Mover's Distance for perceptually meaningful visual saliency
… statistical model and studies what effects the histogram construction method and histogram distance measures have on detecting saliency. Equi-width histograms, which have constant bin size, equi-depth histograms, which have constant density per bin, and diagonal histograms, whose bin widths are …
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Moment Constraints in Radiation Therapy Planning Optimization Incorporating Patient-Specific Anatomical Geometry
… structures. In inverse planning, dose-volume histogram (DVH) is a key concept for measuring and restricting collateral radiation damage to healthy tissues. Interpreting the DVH as a probability distribution, a framework is proposed to assess the deviation from a reference dose-volume histogram …
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High performance histogramming on massively parallel processors
Histogramming is a technique by which input datasets are mined to extract features and patterns. Histograms have wide range of uses in computer vision, machine learning, database processing, quality control for manufacturing, and many applications benefit from advance knowledge about the …
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Recognition and Orientation of Specular Objects from the Analysis of Plane Polarised Light
… description of the object takes the form of a histogram. The cells of the histogram represent surface orientations, and the frequency in each cell is the visible area of the object at that orientation.<br/><br/>This sensed histogram is compared with a database of pre-computed, viewer-centred, …
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A Joint Dictionary-Based Single-Image Super-Resolution Model
… of further improvement, we also add a gradient histogram preservation term in the sparse model of NCSR, and modify the reference histogram estimation by a simple edge detection based enhancement so that the estimated histogram will be closer to the ground truth. The experimental results …
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Batch Query Memory Prediction Using Deep Query Template Representations
… characteristics into pre-built templates. A histogram representation of these templates is generated for the workload, and a regressor predicts the resource demand, specifically memory cost, based on this histogram. Experimental results using three database benchmarks demonstrate a 47.6% …
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Multiple radar environment emission deinterleaving and PRI prediction
… were sequence search (SS), TOA difference histogram, CDIF, SDIF, CDIF with SS (CDIF SS), SDIF with SS (SDIF SS) and interleaved pulse train spectrum estimation. The interleaved pulse train spectrum estimation algorithm results could not be replicated and were not included in simulations. …
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An attention-enhanced student–teacher framework for structural and logical anomaly detection in industrial settings
… for fine-grained analysis. Additionally, a patch histogram module measures the frequency distribution of components, allowing the system to detect irregularities in their occurrence. During inference, anomaly scores from the histogram module and the fused local–global networks are combined to …
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Hierarchical density estimation for image classification
"Histogram (bag-of-words) and Gaussian mixture models (GMMs) have been widely used in patch-based image classification problems. Despite the satisfactory results reported, both methods suffer from a number of disadvantages. For instance, a histogram may be easy to learn but has a large quantization …
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Analysis of Contrast Enhancement Methods for Infrared Images
… were each compared to the classical technique of histogram equalization using metrics of computational time, histogram standard deviation, sharpness and user observations. These metrics provide both quantitative and qualitative analyses of the implemented techniques which are relevant to the end …
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Robust Number Plate Detection Algorithms
… algorithms for classifying number plate colours. Histogram-based image matching methods are investigated, and a Gaussian Weighted Histogram Intersection (GWHI) algorithm is presented. This algorithm is shown to be much more robust against various colour variations than previous methods. …
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Improving individual identification of wolves (Canis lupus) using the fundamental frequency and amplitude of their howls: a new survey method
… code to extract the howl features, combined with histogram-derived principal component analysis (PCA) values, can improve current individual wolf howl identification accuracies. From a total of 89 solo howls from six captive individuals, where distances between wolf and observer were short, I …
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Action recognition via sequence embedding
… representation method, such as edge detection, Histogram of Oriented Gradients (HOG) and Histogram of Optical Flow (HOF). After capturing shape and motion features, salient weak classifiers are picked up by AdaBoost algorithm. Our approach enables robust action recognition in very challenging …
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