Search results for " vision"

showing 10 items of 2709 documents

Evaluation of image processing technique as an expert system in mulberry fruit grading based on ripeness level using artificial neural networks (ANNs…

2020

Abstract Image processing and artificial intelligence (AI) techniques have been applied to analyze, evaluate and classify mulberry fruit according to their ripeness (unripe, ripe, and overripe). A total of 577 mulberries were graded by an expert and the images were captured by an imaging system. Then, the geometrical properties, color, and texture characteristics of each segmented mulberry was extracted using two feature reduction methods: Correlation-based Feature Selection subset (CFS) and Consistency subset (CONS). Artificial Neural Networks (ANN) and Support Vector Machine (SVM) were applied to classify mulberry fruit. ANN classification with the CFS subset feature extraction method res…

0106 biological sciencesArtificial neural networkbusiness.industryFeature extractionPattern recognitionFeature selectionImage processing04 agricultural and veterinary sciencesHorticulturecomputer.software_genreRipeness01 natural sciencesExpert system040501 horticultureMachine vision systemSupport vector machineArtificial intelligence0405 other agricultural sciencesbusinessAgronomy and Crop Sciencecomputer010606 plant biology & botanyFood ScienceMathematicsPostharvest Biology and Technology
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Benchmark database for fine-grained image classification of benthic macroinvertebrates

2018

Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and proportion of certain species. This paper presents a benchmark database for automatic visual classification methods to evaluate their ability for distinguishing visually similar categories of aquatic macroinvertebrate taxa. We make publicly available a new database, containing 64 types of freshwater macroinvertebrates, ranging in number of images per category from 7 to 577. The database is divided into three datasets, varying in number of categories (64, 29, and 9 categori…

0106 biological sciencesComputer scienceta1172Sample (statistics)monitorointi02 engineering and technologyneuroverkot01 natural sciencesConvolutional neural network0202 electrical engineering electronic engineering information engineeringkonenäköfine-grained classification14. Life underwaterFine-grained classificationInvertebrateta113ta112Contextual image classificationbusiness.industry010604 marine biology & hydrobiologyDeep learningConvolutional Neural NetworksBenchmark databasedeep learningPattern recognitionDeep learningselkärangattomatvedenlaatu6. Clean waterkoneoppiminenBenthic zoneBenthic macroinvertebratesbiomonitoringSignal ProcessingBiomonitoringta1181lajinmääritys020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionArtificial intelligenceWater qualitybusinessbenthic macroinvertebrates
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A nondestructive intelligent approach to real‐time evaluation of chicken meat freshness based on computer vision technique

2019

In this study, the capability of a procedure based on combination of computer vision (CV) and artificial intelligence techniques examined for intelligent and nondestructive prediction of chicken meat freshness during the spoilage process at 4°C. The proposed system comprises the following stages: capture images, image preprocessing, image processing, computing channels, feature extraction, feature selection by a hybrid of genetic algorithm (GA) and artificial neuronal network (ANN), and prediction by using ANN. The number of neurons in input layer was determined 33 (selected features) and freshness used as the output. The ideal ANN model was obtained with 33‐10‐1 topology. The high performa…

0106 biological sciencesCorrelation coefficientbusiness.industryComputer scienceGeneral Chemical Engineeringmedia_common.quotation_subjectFeature extractionProcess (computing)Image processingFeature selection04 agricultural and veterinary sciences040401 food science01 natural sciences0404 agricultural biotechnology010608 biotechnologyGenetic algorithmPreprocessorQuality (business)Computer visionArtificial intelligencebusinessFood Sciencemedia_commonJournal of Food Process Engineering
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Temperate Fish Detection and Classification: a Deep Learning based Approach

2021

A wide range of applications in marine ecology extensively uses underwater cameras. Still, to efficiently process the vast amount of data generated, we need to develop tools that can automatically detect and recognize species captured on film. Classifying fish species from videos and images in natural environments can be challenging because of noise and variation in illumination and the surrounding habitat. In this paper, we propose a two-step deep learning approach for the detection and classification of temperate fishes without pre-filtering. The first step is to detect each single fish in an image, independent of species and sex. For this purpose, we employ the You Only Look Once (YOLO) …

0106 biological sciencesFOS: Computer and information sciencesComputer Science - Machine LearningComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern Recognition010603 evolutionary biology01 natural sciencesConvolutional neural networkVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420Machine Learning (cs.LG)Artificial IntelligenceClassifier (linguistics)FOS: Electrical engineering electronic engineering information engineeringbusiness.industry010604 marine biology & hydrobiologyDeep learningImage and Video Processing (eess.IV)Process (computing)Pattern recognitionElectrical Engineering and Systems Science - Image and Video ProcessingObject detectionA priori and a posterioriNoise (video)Artificial intelligenceTransfer of learningbusiness
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Developing an orientation and cutting point determination algorithm for a trout fish processing system using machine vision

2019

Abstract Fish processing in small and medium fish supplying centers requires an intelligent system to operate on different sizes. Therefore, an image processing algorithm was developed to extract the proper head and belly cutting points according to the trout dimensions. The algorithm detects the fish orientation and location of pectoral, anal, pelvic, and caudal fins. In this study, each of the trout images was divided into slices along its length in order to segment the fins and extract cutting points. The channel ‘B’ of RGB color space was considered in both initial segmentation and fin detection stages among the examined channels of RGB, HSV, and L*a*b* color spaces. The back-belly and …

0106 biological sciencesFinbiologyOrientation (computer vision)ForestryImage processing04 agricultural and veterinary sciencesHSL and HSVHorticultureColor spacebiology.organism_classification01 natural sciencesComputer Science ApplicationsRGB color spaceTrout040103 agronomy & agriculture0401 agriculture forestry and fisheriesRGB color modelAgronomy and Crop ScienceAlgorithm010606 plant biology & botanyMathematicsComputers and Electronics in Agriculture
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Odor intensity measurements in gas chromatography-olfactometry using cross modality matching : evaluation of training effects

1999

International audience

0106 biological sciencesMatching (statistics)Cross modalityComputer sciencebusiness.industry[SPI.GPROC] Engineering Sciences [physics]/Chemical and Process Engineering04 agricultural and veterinary sciences[SDV.IDA] Life Sciences [q-bio]/Food engineering040401 food science01 natural sciences3. Good healthIntensity (physics)0404 agricultural biotechnologyOdor010608 biotechnologyOlfactometry[SDV.IDA]Life Sciences [q-bio]/Food engineeringINTENSITEComputer vision[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process EngineeringGas chromatographyArtificial intelligencebusinessComputingMilieux_MISCELLANEOUSAPPARIEMENT CROSS-MODAL
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Discrimination of common defects in loquat fruit cv. ‘Algerie’ using hyperspectral imaging and machine learning techniques

2021

Abstract Loquat (Eriobotrya japonica L.) is an important fruit for the economy of some regions of Spain that is very susceptible to mechanical damage and physiological disorders. These problems depreciate its value and prevent it from being exported. Visible (VIS) and near infrared (NIR) hyperspectral imaging was used to discriminate between external and internal common defects of loquat cv. ‘Algerie’. Two classifiers, random forest (RF) and extreme gradient boost (XGBoost), and different spectral pre-processing techniques were evaluated in terms of their capacity to distinguish between sound and defective features according to three approaches. In the first approach the fruit pixels were c…

0106 biological sciencesN01 Agricultural engineeringEriobotryaHorticulture01 natural sciences040501 horticultureNon-destructiveClassification rateH20 Plant diseasesArtificial visionMathematicsPixelbiologybusiness.industryHyperspectral imagingPattern recognition04 agricultural and veterinary sciencesClassificationbiology.organism_classificationQualityRandom forestEriobotrya japonicaMultivariate analysisN20 Agricultural machinery and equipmentArtificial intelligence0405 other agricultural sciencesbusinessAgronomy and Crop Science010606 plant biology & botanyFood SciencePostharvest Biology and Technology
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Automatic measurement of wood fiber orientation and knot detection using an optical system based on heating conduction.

2015

In this paper, a new approach to computing the deviation of wood grain is proposed. To do this, the thermal conduction properties of timber are used (higher conduction in the fiber direction). Exciting the surface of the wood with a laser and capturing the thermal conduction using a thermal camera, an ellipse can be observed. Using a method similar to the tracheid effect, it is possible to extract information from this ellipse, such as the slope of grain and the presence of knots. With this method it is therefore possible to extend the mechanical model (assessing the mechanical properties of timber) to take certain singularities into account. Using this approach, the slope of grain can be e…

0106 biological sciencesOptical fiberMaterials scienceSoftwoodThermal imaging[ SPI.MECA ] Engineering Sciences [physics]/Mechanics [physics.med-ph]Machine VisionLaserEllipse01 natural sciencesgrain anglelaw.inventionOpticsKnot (unit)law010608 biotechnologyThermalHardwoodOptique / photonique [Sciences de l'ingénieur]040101 forestryMécanique [Sciences de l'ingénieur]business.industry04 agricultural and veterinary sciences[SPI.MECA]Engineering Sciences [physics]/Mechanics [physics.med-ph]Thermal conductionWoodAtomic and Molecular Physics and Optics[SPI.OPTI]Engineering Sciences [physics]/Optics / Photonic0401 agriculture forestry and fisheries[ SPI.OPTI ] Engineering Sciences [physics]/Optics / PhotonicWood grainbusinessOptics express
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New Reptile Hosts for Helminth Parasites in a Mediterranean Region

2020

ABSTRACT Parasitic helminths are an almost universal feature of vertebrate animals, but reptiles are among the hosts with the most depauperate parasite communities. Biological traits of reptiles ar...

0106 biological sciencesParasitic helminthMediterranean climate010607 zoologyVertebrate AnimalsZoologyBiology010603 evolutionary biology01 natural sciencesFeature (computer vision)parasitic diseasesParasite hostingHelminthsAnimal Science and ZoologyEcology Evolution Behavior and SystematicsJournal of Herpetology
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Context-dependent coloration of prey and predator decision making in contrasting light environments

2022

A big question in behavioral ecology is what drives diversity of color signals. One possible explanation is that environmental conditions, such as light environment, may alter visual signaling of prey, which could affect predator decision-making. Here, we tested the context-dependent predator selection on prey coloration. In the first experiment, we tested detectability of artificial visual stimuli to blue tits (Cyanistes caeruleus) by manipulating stimulus luminance and chromatic context of the background. We expected the presence of the chromatic context to facilitate faster target detection. As expected, blue tits found targets on chromatic yellow background faster than on achromatic gre…

0106 biological sciencescognitionvaroitusväriRECEIVER PSYCHOLOGYAVOIDANCEContext (language use)Biologypsychology010603 evolutionary biology01 natural scienceseläinten käyttäytyminentäpläsiilikäsPredation03 medical and health sciencesreceptor-noise-limited modelPredatorsinitiainenEcology Evolution Behavior and Systematics030304 developmental biology0303 health sciencesSENSORY DRIVEEcologybehaviorMOTH15. Life on landLUMINANCEnäköPOLYMORPHISMsaalistusVISIONBIRDcolor vision1181 Ecology evolutionary biologyAnimal Science and ZoologyWARNING SIGNALSsignal
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