Search results for "saliency"

showing 10 items of 41 documents

Experimental comparison of two control algorithms for low-saliency ratio interior permanent magnet synchronous motors

2018

In this paper, an experimental investigation on the comparison between the Maximum Torque Per Ampere (MTPA) and the Field Orientation Control (FOC) algorithms for interior permanent magnet synchronous machines (IPMSMs) is described, analyzed and discussed. This investigation was carried out on a small-power IPMSM with low saliency ratio. More in detail, after a previous simulation study, the control techniques have been experimentally implemented and validated through means of a dSPACE® rapid prototyping system. The performances of the two algorithms have been evaluated and compared, obtaining interesting results.

010302 applied physicsRapid prototypingControl algorithmElectromagneticsPermanent magnet synchronous motorComputer scienceRenewable Energy Sustainability and the Environment020208 electrical & electronic engineeringlow saliency ratio motor02 engineering and technologySettore ING-IND/32 - Convertitori Macchine E Azionamenti Elettrici01 natural sciencesField oriented control algorithmmaximum torque per ampere control algorithmControl theoryMagnet0103 physical sciencesAutomotive Engineering0202 electrical engineering electronic engineering information engineeringTorqueInterior permanent magnet synchronous machineAmpereMaximum torque
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Visual saliency detection in colour images based on density estimation

2017

International audience; A simple and effective method for visual saliency detection in colour images is presented. The method is based on the common observation that local salient regions exhibit distinct geometric and and texture patterns from neighbouring regions. We model the colour distribution of local image patches with a Gaussian density and measure the saliency of each patch as the statistical distance from that density. Experimental results with public datasets and comparison with other state-of-the-art methods show the effectiveness of our method.

0209 industrial biotechnologybusiness.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern recognitionGaussian density02 engineering and technologyDensity estimation[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Measure (mathematics)Texture (geology)020901 industrial engineering & automationSalientComputer Science::Computer Vision and Pattern Recognition0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligenceElectrical and Electronic EngineeringbusinessComputingMethodologies_COMPUTERGRAPHICSVisual saliencyElectronics Letters
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Spatio-temporal saliency detection in dynamic scenes using color and texture features

2014

Visual saliency is an important research topic in the field of computer vision due to its numerouspossible applications. It helps to focus on regions of interest instead of processingthe whole image or video data. Detecting visual saliency in still images has been widelyaddressed in literature with several formulations. However, visual saliency detection invideos has attracted little attention, and is a more challenging task due to additional temporalinformation. Indeed, a video contains strong spatio-temporal correlation betweenthe regions of consecutive frames, and, furthermore, motion of foreground objects dramaticallychanges the importance of the objects in a scene. The main objective o…

Color featureComplex dynamic scenesSpatio-temporal saliencyDynamic texturesFusionPerformance evalutationModèles d'attention visuelle[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing
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Convolutional Neural Network for Blind Mesh Visual Quality Assessment Using 3D Visual Saliency

2018

In this work, we propose a convolutional neural network (CNN) framework to estimate the perceived visual quality of 3D meshes without having access to the reference. The proposed CNN architecture is fed by small patches selected carefully according to their level of saliency. To do so, the visual saliency of the 3D mesh is computed, then we render 2D projections from the 3D mesh and its corresponding 3D saliency map. Afterward, the obtained views are split to obtain 2D small patches that pass through a saliency filter to select the most relevant patches. Experiments are conducted on two MVQ assessment databases, and the results show that the trained CNN achieves good rates in terms of corre…

Computer sciencebusiness.industryQuality assessmentDistortion (optics)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION020207 software engineeringPattern recognition02 engineering and technologyFilter (signal processing)Convolutional neural networkVisualizationSalience (neuroscience)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSaliency mapArtificial intelligencebusinessComputingMethodologies_COMPUTERGRAPHICSVisual saliency2018 25th IEEE International Conference on Image Processing (ICIP)
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Feature selection for distance-based regression: An umbrella review and a one-shot wrapper

2023

Feature selection (FS) may improve the performance, cost-efficiency, and understandability of supervised machine learning models. In this paper, FS for the recently introduced distance-based supervised machine learning model is considered for regression problems. The study is contextualized by first providing an umbrella review (review of reviews) of recent development in the research field. We then propose a saliency-based one-shot wrapper algorithm for FS, which is called MAS-FS. The algorithm is compared with a set of other popular FS algorithms, using a versatile set of simulated and benchmark datasets. Finally, experimental results underline the usefulness of FS for regression, confirm…

EMLMfeature selectionkoneoppiminenArtificial IntelligenceCognitive Neurosciencealgoritmitparantaminen (paremmaksi muuttaminen)tekoälydistance-based methodwrapper algorithmfeature saliencyComputer Science ApplicationsNeurocomputing
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Combining Top-down and Bottom-up Visual Saliency for Firearms Localization

2014

Object detection is one of the most challenging issues for computer vision researchers. The analysis of the human visual attention mechanisms can help automatic inspection systems, in order to discard useless information and improving performances and efficiency. In this paper we proposed our attention based method to estimate firearms position in images of people holding firearms. Both top-down and bottom-up mechanisms are involved in our system. The bottom-up analysis is based on a state-of-the-art approach. The top-down analysis is based on the construction of a probabilistic model of the firearms position with respect to the people’s face position. This model has been created by analyzi…

Firearms Detection Visual Saliency Probabilistic Model.Computer sciencebusiness.industryStatistical modelTop-down and bottom-up designObject detectionPosition (vector)Face (geometry)Visual attentionComputer visionArtificial intelligencebusinessVisual saliencyProceedings of the 11th International Conference on Signal Processing and Multimedia Applications
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A Multi-Scale Colour and Keypoint Density-Based Approach for Visual Saliency Detection

2020

In the first seconds of observation of an image, several visual attention processes are involved in the identification of the visual targets that pop-out from the scene to our eyes. Saliency is the quality that makes certain regions of an image stand out from the visual field and grab our attention. Saliency detection models, inspired by visual cortex mechanisms, employ both colour and luminance features. Furthermore, both locations of pixels and presence of objects influence the Visual Attention processes. In this paper, we propose a new saliency method based on the combination of the distribution of interest points in the image with multiscale analysis, a centre bias module and a machine …

General Computer ScienceComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONinterest pointsLuminanceSalience (neuroscience)medicineVisual attentionGeneral Materials ScienceComputer visionElectrical and Electronic EngineeringVisual saliencySettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniPixelbusiness.industryGeneral EngineeringEye-movementsObject (computer science)saliency mapVisual fieldIdentification (information)Visual cortexmedicine.anatomical_structurevisual attentionEye trackinglcsh:Electrical engineering. Electronics. Nuclear engineeringArtificial intelligenceScale (map)businesslcsh:TK1-9971
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Image Quality Assessment by saliency maps

2012

Image Quality Assessment (IQA) is an interesting challenge for image processing applications. The goal of IQA is to replace human judgement of perceived image quality with a machine evaluation. A large number of methods have been proposed to evaluate the quality of an image which may be corrupted by noise, distorted during acquisition, transmission, compression, etc. Many methods, in some cases, do not agree with human judgment because they are not correlated with human visual perception. In the last years the most modern IQA models and metrics considered visual saliency as a fundamental issue. The aim of visual saliency is to produce a saliency map that replicates the human visual system (…

Image Quality Assessment Visual Saliency Saliency Map Human Visual System Perceptual Quality
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Maximum Torque per Ampere Control strategy for low-saliency ratio IPMSMs

2019

This paper deals with electrical drives employing low-saliency ratio interior permanent magnet synchronous motors. In particular, in order to help the designers choosing the best control algorithm, the performances of the Maximum Torque Per Ampere Control (MTPA) and the Field Orientation Control (FOC) are here both theoretically and experimentally assessed and compared, by using, as performance indicators, the torque-current ratio and the power losses. The tests are carried out on a low-power motor for various speeds and loads by implementing the two control strategies in a dSPACE® rapid prototyping system. The results show that the Maximum Torque Per Ampere algorithm has some appreciable a…

Low saliency ratio machineMTPA control strategySettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciFOC algorithmSettore ING-INF/07 - Misure Elettriche E ElettronicheIPMSM
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Benchmarking Saliency Detection Methods on Multimodal Image Data

2018

Saliency detecmage processing. Most of the work is adapted to the specific application and available dataset. The present work is about a comparative analysis of saliency detection for multimodal images dataset. There were many researches on the detection of saliency on several types of images, such as multispectral, natural, 3D and so on. This work presents a first focused study on saliency detection on multimodal images. Our database was extracted from acquisitions on cultural heritage wall paintings that contain four modalities UV, IR, Visible and fluorescence. In this paper, the analysis has been performed for many methods on saliency detection. We evaluate the performance of each metho…

Modality (human–computer interaction)Similarity (geometry)Computer sciencebusiness.industry05 social sciencesMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPattern recognition02 engineering and technologyBenchmarking050105 experimental psychologyMultimodal imageMetric (mathematics)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing0501 psychology and cognitive sciencesSaliency mapArtificial intelligencebusiness
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