Search results for "object-based"

showing 8 items of 8 documents

Reverse inheritance in statically typed object-oriented programming languages

2010

Reverse inheritance is a new class reuse mechanism, an experimental implementation of which we have built for Eiffel. It enables a more natural design approach, factorization of common features (members), insertion of classes into an existing hierarchy etc. Due to its reuse potential in Eiffel we consider exploring its capabilities in other industrial-strength programming languages like C++, Java and C#.

Composition over inheritanceGeneric programmingComputer scienceProgramming languageMultiple inheritanceObject-based languageSoftware_PROGRAMMINGTECHNIQUESEiffelcomputer.software_genreClass-based programmingInheritance (object-oriented programming)Singly rooted hierarchycomputercomputer.programming_languageProceedings of the 4th Workshop on MechAnisms for SPEcialization, Generalization and inHerItance
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Post-processing of Pixel and Object-Based Land Cover Classifications of Very High Spatial Resolution Images

2020

The state of the art is plenty of classification methods. Pixel-based methods include the most traditional ones. Although these achieved high accuracy when classifying remote sensing images, some limits emerged with the advent of very high-resolution images that enhanced the spectral heterogeneity within a class. Therefore, in the last decade, new classification methods capable of overcoming these limits have undergone considerable development. Within this research, we compared the performances of an Object-based and a Pixel-Based classification method, the Random Forests (RF) and the Object-Based Image Analysis (OBIA), respectively. Their ability to quantify the extension and the perimeter…

PixelComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONObject basedLand coverClass (biology)Random forestObject-Based image analysisRemote sensing (archaeology)Computer Science::Computer Vision and Pattern RecognitionVector based generalizationHigh spatial resolutionObject-Based image analysis; Random forest; Vector based generalizationState (computer science)Settore ICAR/06 - Topografia E CartografiaRandom forestRemote sensing
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Classification of Plant Ecological Units in Heterogeneous Semi-Steppe Rangelands: Performance Assessment of Four Classification Algorithms.

2021

Plant Ecological Unit’s (PEUs) are the abstraction of vegetation communities that occur on a site which similarly respond to management actions and natural disturbances. Identification and monitoring of PEUs in a heterogeneous landscape is the most difficult task in medium resolution satellite images datasets. The main objective of this study is to compare pixel-based classification versus object-based classification for accurately classifying PEUs with four selected different algorithms across heterogeneous rangelands in Central Zagros, Iran. We used images of Landsat-8 OLI that were pan-sharpened to 15 m to classify four PEU classes based on a random dataset collected in the field (40%). …

PixelEcologyComputer scienceprincipal component analysisScienceQPerceptronObject (computer science)Field (computer science)Statistical classificationplant ecological units mappingmachine learning algorithmsPrincipal component analysisClassifier (linguistics)General Earth and Planetary Sciencesobject-based classificationTest dataRemote sensing
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On the Choice of the Most Suitable Period to Map Hill Lakes via Spectral Separability and Object-Based Image Analyses

2023

Technological advances in Earth observation made images characterized by high spatial and temporal resolutions available, nevertheless bringing with them the radiometric heterogeneity of small geographical entities, often also changing in time. Among small geographical entities, hill lakes exhibit a widespread distribution, and their census is sometimes partial or shows unreliable data. High resolution and heterogeneity have boosted the development of geographic object-based image analysis algorithms. This research analyzes which is the most suitable period for acquiring satellite images to identify and delimitate hill lakes. This is achieved by analyzing the spectral separability of the su…

Regionalizationregionalization; geographic object-based image analysis; Euclidean distance; divergence; hill lakeshill lakesgeographic object-based image analysiGeneral Earth and Planetary SciencesEuclidean distancedivergenceSettore ICAR/06 - Topografia E CartografiaRemote Sensing
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Exploiting Visual Saliency Algorithms for Object-Based Attention: A New Color and Scale-Based Approach

2017

Visual Saliency aims to detect the most important regions of an image from a perceptual point of view. More in detail, the goal of Visual Saliency is to build a Saliency Map revealing the salient subset of a given image by analyzing bottom-up and top-down factors of Visual Attention. In this paper we proposed a new method for Saliency detection based on colour and scale analysis, extending our previous work based on SIFT spatial density inspection. We conducted several experiments to study the relationships between saliency methods and the object attention processes and we collected experimental data by tracking the eye movements of thirty viewers in the first three seconds of observation o…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniComputer sciencebusiness.industrymedia_common.quotation_subject05 social sciencesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONEye movementExperimental dataScale-invariant feature transformVisual saliency Object-based attention SIFT Fixation maps Dataset Eye trackingPattern recognition02 engineering and technology050105 experimental psychologySalientPerceptionFixation (visual)0202 electrical engineering electronic engineering information engineeringEye tracking020201 artificial intelligence & image processing0501 psychology and cognitive sciencesComputer visionArtificial intelligencebusinessObject-based attentionmedia_common
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A nonstationary cylinder-based model describing group dispersal in a fragmented habitat

2014

International audience; A doubly nonstationary cylinder-based model is built to describe the dispersal of a population from a point source. In this model, each cylinder represents a fraction of the population, i.e., a group. Two contexts are considered: The dispersal can occur in a uniform habitat or in a fragmented habitat described by a conditional Boolean model. After the construction of the models, we investigate their properties: the first and second order moments, the probability that the population vanishes, and the distribution of the spatial extent of the population.

Statistics and ProbabilityPoint sourcePopulation92D25Spatial extentFragmentationStatisticsRandom cylinder92D30CylinderQuantitative Biology::Populations and EvolutionObject-based model[INFO]Computer Science [cs]Statistical physics60D05[MATH]Mathematics [math]educationMathematics60G60ta112education.field_of_studyBoolean modelApplied MathematicsFragmentation (computing)Boolean modelDispersal60K37HabitatModeling and Simulation60K9992D40Biological dispersalPopulation vanishing60G55Distribution (differential geometry)
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Object-based image analysis technique for gully mapping using topographic data at very high resolution (VHR)

2018

An accurate mapping of gullies is important since they are still major contributors of sediment to streams. Mapping gullies can be difficult because of the presence of dense canopy, which precludes the identification through aerial photogrammetry and other traditional remote sensing methods. Moreover, the wide spatial extent of some gullies makes their identification and characterization through field surveys a very large and expensive proposition. One cheaper and more expeditious way to detect gullies can be achieved in terms of morphological characteristics by the Digital Elevation Models (DEMs). The recent widespread availability of very high resolution (VHR) imagery, such as LIDAR data,…

Very high resolutionObject-based very high resolution segmentation classification eCognitionobject-based very high resolution segmentation classification eCognitionSettore ICAR/02 - Costruzioni Idrauliche E Marittime E IdrologiaObject basedGeologyImage (mathematics)Remote sensing
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Developing and comparing methods for mapping habitat types and conservation values using remote sensing data and GIS methods

2014

segmentationairborne laser scanningconservation valuehabitaattiobjektiperustainen kuva-analyysielinympäristötyypitsegmentointilajirunsauselinympäristöluokitteluobject-based image analysishabitat typespectral imageskaukokartoitusspecies richnessmetsämaisemapaikkatietomenetelmätsuojeluarvotluokittelumenetelmätlaserkeilaus
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