Search results for " recognition"

showing 10 items of 3220 documents

In situ Phenotyping of Grapevine Root System Architecture by 2D or 3D Imaging: Advantages and Limits of Three Cultivation Methods

2021

International audience; The root system plays an essential role in the development and physiology of the plant, as well as in its response to various stresses. However, it is often insufficiently studied, mainly because it is difficult to visualize. For grapevine, a plant of major economic interest, there is a growing need to study the root system, in particular to assess its resistance to biotic and abiotic stresses, understand the decline that may affect it, and identify new ecofriendly production systems. In this context, we have evaluated and compared three distinct growing methods (hydroponics, plane, and cylindric rhizotrons) in order to describe relevant architectural root traits of …

0106 biological sciences0301 basic medicineRoot (linguistics)phenotypingContext (language use)Root systemPlant ScienceBiologyrhizotron01 natural sciencesSkeletonizationSB1-111003 medical and health sciencesCutting[SDV.SA.STA]Life Sciences [q-bio]/Agricultural sciences/Sciences and technics of agricultureMethods2. Zero hungerroot system architectureNeutron tomographyRhizotronPlant culture[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]15. Life on landHydroponicsgrapevine2D/3D imaging030104 developmental biologyroot traitsneutron tomographyBiological system010606 plant biology & botanyFrontiers in Plant Science
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Variable crab camouflage patterns defeat search image formation.

2021

Understanding what maintains the broad spectrum of variation in animal phenotypes and how this influences survival is a key question in biology. Frequency dependent selection – where predators temporarily focus on one morph at the expense of others by forming a “search image” – can help explain this phenomenon. However, past work has never tested real prey colour patterns, and rarely considered the role of different types of camouflage. Using a novel citizen science computer experiment that presented crab “prey” to humans against natural backgrounds in specific sequences, we were able to test a range of key hypotheses concerning the interactions between predator learning, camouflage and mor…

0106 biological sciences0301 basic medicineTime FactorsComputer scienceQH301-705.5BrachyuraBehavioural ecologyFrequency-dependent selectionMedicine (miscellaneous)ColorVariation (game tree)010603 evolutionary biology01 natural sciencesGeneral Biochemistry Genetics and Molecular BiologyArticlePredationtaskuravut03 medical and health sciencesDisruptive colorationCitizen scienceAnimalsHumansexperimental evolutionBiology (General)muuntelu (biologia)PredatorEcosystemsuojaväriMechanism (biology)Pigmentationbehavioural ecologyAdaptation Physiological030104 developmental biologyPhenotypeVideo GamesExperimental evolutionEvolutionary biologyCamouflagePattern Recognition PhysiologicalPredatory BehaviorfenotyyppiGeneral Agricultural and Biological SciencesColor PerceptionCommunications biology
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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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Biometric Fish Classification of Temperate Species Using Convolutional Neural Network with Squeeze-and-Excitation

2019

Our understanding and ability to effectively monitor and manage coastal ecosystems are severely limited by observation methods. Automatic recognition of species in natural environment is a promising tool which would revolutionize video and image analysis for a wide range of applications in marine ecology. However, classifying fish from images captured by underwater cameras is in general very challenging due to noise and illumination variations in water. Previous classification methods in the literature relies on filtering the images to separate the fish from the background or sharpening the images by removing background noise. This pre-filtering process may negatively impact the classificat…

0106 biological sciencesBiometricsComputer sciencebusiness.industry010604 marine biology & hydrobiologyPattern recognitionSharpening010603 evolutionary biology01 natural sciencesConvolutional neural networkBackground noiseA priori and a posterioriArtificial intelligenceUnderwaterbusinessTransfer of learningClassifier (UML)
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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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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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Risk of inbreeding : problem of mate choice and fitness effects?

2016

Mating with close kin may cause inbreeding depression with negative consequences to offspring and local populations. There exist mechanisms like kin-recognition or sex-specific dispersal to avoid mating with kin. In fluctuating population densities, like in many small mammals, both very low and very high densities provide conditions for inbreeding, if kin males are prone to stay in their natal area. Females are choosy and male dominance is thought to be the key feature when selecting mating partners. The aim of this study was to test the possible discrepancy in mate choice and negative fitness effects of inbreeding in two experiments, one in the laboratory and one in field enclosures. We as…

0106 biological sciencesKin recognitionOffspringBiologydominance010603 evolutionary biology01 natural sciencesPopulation densityInbreeding depression0501 psychology and cognitive sciences050102 behavioral science & comparative psychologydispersalEcology Evolution Behavior and Systematicskin recognitionEcology05 social sciencesMate choicebehavior and behavior mechanismsBiological dispersalta1181Animal Science and ZoologyFitness effectsInbreedingDemographyClethrionomysinbreeding depressionIsrael Journal of Ecology and Evolution
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Chemical fingerprints suggest direct familiarisation rather than phenotype matching during olfactory recognition in Australian sea lions (Neophoca ci…

2019

International audience; Olfaction is one of the most commonly used senses for communication among animals and is of particular importance to mother-offspring recognition in mammals. The use of smell in offspring recognition has been well studied, however, we often lack information about the underlying mechanistic basis for olfactory recognition. Using gas chromatography–mass spectrometry (GC–MS), we examine chemical profiles of two different colonies of Australian sea lions (Neophoca cinerea) and assess similarity of chemical fingerprints in mother-pup pairs. This analysis allows us to examine whether a chemical base for phenotype matching exists in this species. Our results showed no GC-de…

0106 biological sciencesMatching (statistics)biology[SDV.NEU.PC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behavior010604 marine biology & hydrobiology[SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/NeurobiologyPinniped Neophoca cinerea[SDV.NEU.SC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive SciencesNeophoca cinereaOlfactionMother-offspring recognitionAquatic Sciencebiology.organism_classificationChemical communication010603 evolutionary biology01 natural sciencesPhenotypeOlfactionChemical communicationEvolutionary biologySea lionEcology Evolution Behavior and Systematics
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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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The role of partial incubation and egg repositioning within the clutch in hatching asynchrony and subsequent effects on breeding success

2019

The main mechanism to achieve hatching asynchrony (HA) for incubating birds is to start heating the eggs before clutch completion. This might be achieved through partial incubation and/or early incubation. Even in the absence of incubation behaviour during the laying phase, clutches still experience a certain degree of asynchrony. Recent studies have shown that eggs located in the centre of the nest receive more heat than peripheral ones during incubation. As eggs receiving more heat would develop faster, we hypothesized that HA should be shorter in nests where eggs were moved homogeneously along the centre–periphery space during incubation than in those nests where eggs repeatedly remained…

0106 biological sciencesParusbiologyFledgeEgg recognitionEgg turningbiology.organism_classification010603 evolutionary biology01 natural sciencesBrood010605 ornithologyIncubation periodAnimal scienceNestGreat TitsHatching asynchronyembryonic structuresAnimal Science and ZoologyClutchIncubation periodIncubationThermal gradientsEcology Evolution Behavior and SystematicsIbis
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