Search results for "Artificial"

showing 10 items of 7394 documents

The iterative object symmetry transform

2005

This paper introduces a new operator named the Iterated Object Transform that is computed by combining the Object Symmetry Transform with the morphological operator erosion. This new operator has been applied on both binary and gray levels images showing the ability to grasp the internal structure of a digital object. We present some experiments on real images in face analysis.

business.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONObject (computer science)Erosion (morphology)Object detectionObject-class detectionsymbols.namesakeOperator (computer programming)Fourier transformsymbolsComputer visionViola–Jones object detection frameworkArtificial intelligenceSymmetry (geometry)businessMathematics2004 International Conference on Image Processing, 2004. ICIP '04.
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Saliency Based Aesthetic Cut of Digital Images

2013

Aesthetic cut of photos is a process well known to professional photographers. It consists of cutting the original photo to remove less relevant parts close to the borders leaving in this way the interesting subjects in a position that is perceived by the observer as more pleasant. In this paper we propose a saliency based technique to automatically perform aesthetic cut in images. We use a standard method to estimate the saliency map and propose some post processing on the map to make it more suitable for our scope. We then apply a greedy algorithm to determine the cut (i.e. the most important part of the original image) both in the cases of free and fixed aspect ratio. Experimental result…

business.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONObserver (special relativity)Image editingcomputer.software_genreDigital imageRetargetingAesthetic cut image editing saliency.Saliency mapComputer visionArtificial intelligencebusinessGreedy algorithmcomputerMathematics
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Splitting criterion for hierarchical motion estimation based on perceptual coding

1998

A new entropy-constrained motion estimation scheme using variable-size block matching is proposed. It is known that fixed-size block matching as used in most video codec standards is improved by using a multiresolution or multigrid approach. In this work, it is shown that further improvement is possible in terms of both the final bit rate achieved and the robustness of the predicted motion field if perceptual coding is taken into account in the motion estimation phase. The proposed scheme is compared against other variable- and fixed-size block matching algorithms.

business.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionQuarter-pixel motionMultigrid methodMotion fieldRobustness (computer science)Motion estimationComputer Science::MultimediaBit ratePerceptual codingCodecArtificial intelligenceElectrical and Electronic EngineeringbusinessMathematics
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Acquisition of Higher Order Knowledge by a Dynamic Modeling Environment Based on the Educational Concept of Self-Regulated Learning

2013

I aim to show that learning with this modeling based Educational Learning System (ELS) can accomplish the target of achieving higher order knowledge. The ELS is a system consisting of internal and external elements. The external prerequisites consist of technical and physical elements and the internal ones are shaped by the students pre-knowledge and the instructors teaching competencies including his/her social, emotional, and disciplinary knowledge necessary for teaching. The ELS is based on a theoretical framework of different theories and models such as concept mapping, elaboration of mental models, cognitive tool-approach, and self-regulated learning (SRL). Different features for visua…

business.industryConcept mapComputer scienceCognitionNotationcomputer.software_genreExpression (mathematics)VisualizationHuman–computer interactionFeature (machine learning)Artificial intelligenceRepresentation (mathematics)businessSelf-regulated learningcomputerNatural language processing
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Diversity in search strategies for ensemble feature selection

2005

Ensembles of learnt models constitute one of the main current directions in machine learning and data mining. Ensembles allow us to achieve higher accuracy, which is often not achievable with single models. It was shown theoretically and experimentally that in order for an ensemble to be effective, it should consist of base classifiers that have diversity in their predictions. One technique, which proved to be effective for constructing an ensemble of diverse base classifiers, is the use of different feature subsets, or so-called ensemble feature selection. Many ensemble feature selection strategies incorporate diversity as an objective in the search for the best collection of feature subse…

business.industryContext (language use)Feature selectionMachine learningcomputer.software_genreEnsemble learningMeasure (mathematics)Random subspace methodEnsembles of classifiersComputingMethodologies_PATTERNRECOGNITIONHardware and ArchitectureFeature (computer vision)Signal ProcessingArtificial intelligenceData miningbusinesscomputerSoftwareSelection (genetic algorithm)Information SystemsMathematics
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Robustness of texture parameters for color texture analysis

2006

This article proposes to deal with noisy and variable size color textures. It also proposes to deal with quantization methods and to see how such methods change final results. The method we use to analyze the robustness of the textures consists of an auto-classification of modified textures. Texture parameters are computed for a set of original texture samples and stored into a database. Such a database is created for each quantization method. Textures from the set of original samples are then modified, eventually quantized and classified according to classes determined from a precomputed database. A classification is considered incorrect if the original texture is not retrieved. This metho…

business.industryCovariance matrixAutocorrelationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognitionMaxima and minimaQuantization (physics)Matrix (mathematics)Computer Science::GraphicsAutocorrelation matrixComputer Science::Computer Vision and Pattern RecognitionPrincipal component analysisRGB color modelComputer visionArtificial intelligencebusinessComputingMethodologies_COMPUTERGRAPHICSMathematicsSPIE Proceedings
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<title>Distance functions in dynamic integration of data mining techniques</title>

2000

One of the most important directions in the improvement of data mining and knowledge discovery is the integration of multiple data mining techniques. An integration method needs to be able either to evaluate and select the most appropriate data mining technique or to combine two or more techniques efficiently. A recent integration method for the dynamic integration of multiple data mining techniques is based on the assumption that each of the data mining techniques is the best one inside a certain subarea of the whole domain area. This method uses an instance-based learning approach to collect information about the competence areas of the mining techniques and applies a distance function to…

business.industryData stream miningComputer scienceFeature selectionMachine learningcomputer.software_genreData modelingInformation extractionKnowledge extractionMetric (mathematics)Artificial intelligenceData miningbusinesscomputerInformation integrationData integrationSPIE Proceedings
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Plenoptic image watermarking to preserve copyright

2017

Common camera loses a huge amount of information obtainable from scene as it does not record the value of individual rays passing a point and it merely keeps the summation of intensities of all the rays passing a point. Plenoptic images can be exploited to provide a 3D representation of the scene and watermarking such images can be helpful to protect the ownership of these images. In this paper we propose a method for watermarking the plenoptic images to achieve this aim. The performance of the proposed method is validated by experimental results and a compromise is held between imperceptibility and robustness.

business.industryData_MISCELLANEOUSComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION020207 software engineering02 engineering and technologyÒpticaImage (mathematics)GeographyRobustness (computer science)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPoint (geometry)Computer visionArtificial intelligencebusinessRepresentation (mathematics)Digital watermarkingThree-Dimensional Imaging, Visualization, and Display 2017
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Remote Sensing Geometric Corrections

2016

This article reviews the different aspects of geometrical processing of remote sensing data, discussing error sources and methods to determine the transformation from the image acquisition geometry to the output cartographic product. Resampling methods are discussed to transform the input image to the output geometry. Several practical examples of remote sensing platforms are discussed, including satellite cases and airborne sensors. Validation of the resulting geometrical processed products is also discussed. Spatial mosaicking techniques and multitemporal composites used to produce multisource integrated products and advanced applications are finally considered, keeping a perspective on t…

business.industryDistortion (optics)Perspective (graphical)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage registrationGeographyTransformation (function)Remote sensing (archaeology)Image scalingGlobal Positioning SystemPreprocessorComputer visionArtificial intelligencebusinessRemote sensing
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Dynamics of Vertebral Column Observed by Stereovision and Recurrent Neural Network Model

2005

A new non-invasive method for investigation of movement of selected points on the vertebral column is presented. The registration of position of points marked on patient's body is performed by 4 infrared cameras. This experiment enables to reconstruct 3-dimensional trajectories of displacement of marked points. We introduce recurrent neural networks as formal nonlinear dynamical models of each point trajectory. These models are based only on experimental data and are set up of minimal number of parameters. Therefore they are suitable for pattern recognition problems.

business.industryDynamics (mechanics)Displacement (vector)Set (abstract data type)Nonlinear systemRecurrent neural networkmedicine.anatomical_structurePosition (vector)Pattern recognition (psychology)medicineComputer visionArtificial intelligencebusinessVertebral columnMathematics
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