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Image Recognition : A Complete Guide - Deepomatic

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Image recognition, a subcategory of Computer Vision and Artificial Intelligence, represents a set of methods for detecting and analyzing ... Solutions ByIndustry Telecommunications Utilities Cross-industry ByUseCases Dataintegrity Incidentalwork Physicalobservability Qualitycontrol Workacceptance VisualAutomationForTelecomNetworks WatchNow Platform Customers Company About SustainableAI ResponsibleAI Blog WhitePapers Menu About SustainableAI ResponsibleAI Blog WhitePapers EstimatingTheCarbonFootprintOfAnEnterpriseSoftware Download EN FR Careers Contact Whatisimagerecognition? byEwan01/8/2019 Theemergenceofartificialintelligenceopensthewaytonewdevelopmentpotentialforourindustriesandbusinesses.Moreandmore,companiesareusingComputerVision,andinparticularimagerecognition,toimprovetheirprocessesandincreasetheirproductivity.Sowedecidedtoexplaintoyouinafewwordswhatimagerecognitionis,howitworksanditsdifferentuses. Whatisimagerecognition? Imagerecognition,asubcategoryofComputerVisionandArtificialIntelligence,representsasetofmethodsfordetectingandanalyzingimagestoenabletheautomationofaspecifictask.Itisatechnologythatiscapableofidentifyingplaces,people,objectsandmanyothertypesofelementswithinanimage,anddrawingconclusionsfromthembyanalyzingthem. >>>Ifyouareinterestedinthistopic,seeourarticleexplainingthedifferencebetweenimagerecognitionandcomputervision. Photoorvideorecognitioncanbeperformedatdifferentdegreesofaccuracy,dependingonthetypeofinformationorconceptrequired.Indeed,amodeloralgorithmiscapableofdetectingaspecificelement,justasitcansimplyassignanimagetoalargecategory. Sotherearedifferent“tasks”thatimagerecognitioncanperform: Classification.Itistheidentificationofthe“class”,i.e.thecategorytowhichanimagebelongs.Animagecanhaveonlyoneclass. Tagging.Itisalsoaclassificationtaskbutwithahigherdegreeofaccuracy.Itcanrecognizethepresenceofseveralconceptsorobjectswithinanimage.Oneormoretagscanthereforebeassignedtoaparticularimage. Detection.Thisisnecessarywhenyouwanttolocateanobjectinanimage.Oncetheobjectislocated,aboundingboxisplacedaroundtheobjectinquestion. Segmentation.Thisisalsoadetectiontask.Segmentationcanlocateanelementonanimagetothenearestpixel.Forsomecases,itisnecessarytobeextremelyprecise,asforthedevelopmentofautonomouscars. Howdoesimagerecognitionwork? Imagerecognitionintheory Theoretically,imagerecognitionisbasedonDeepLearning.DeepLearning,asubcategoryofMachineLearning,referstoasetofautomaticlearningtechniquesandtechnologiesbasedonartificialneuralnetworks. Butwhatisanartificialneuralnetwork? Anartificialneuralnetworkissimilartoahumanneuralnetwork,howeveranartificialneuronisamathematicalfunction!Keepinmindthatanartificialneuralnetworkconsistsofaninput,parametersandanoutput. Eachnetworkconsistsofseverallayersofneurons,whichcaninfluenceeachother.Thecomplexityofthearchitectureandstructureofaneuralnetworkwilldependonthetypeofinformationrequired. Itisthankstotheseneuralnetworksthatanalgorithmisabletorecognizeaconceptwithinanimage! Imagerecognitioninpractice Inpractice,forneuralnetworkstorecognizeoneormoreconceptsinanimage,itisnecessarytotrainthem.Todothis,afirstsetofvisualdatamustbecollectedandconstitutedtoserveasabasisfortraining. [Keepinmindthatimagerecognitionworksbyanalyzingeachpixelofanimagetoextractinformation,justlikeahumaneyedoes.Therefore,ifyouarenotabletounderstandtheinformationinaphoto,yourmodelwon’tbeabletoeither!] Oncethedatasethasbeencreated,itisessentialtoannotateit,i.e.tellyourmodelwhetherornottheelementyouarelookingforispresentonanimage,aswellasitslocation.Notethattherearedifferenttypesoflabels(tags,boundingboxesorpolygons)dependingonthetaskyouhavechosen. Onlyoncetheentiredatasethasbeenannotatedisitpossibletomoveontotraining.Aswithahumanbrain,theneuralnetworkmustbetaughttorecognizeaconceptbyshowingitmanydifferentexamples. Thefinalgoalofthetrainingisthatthealgorithmcanmakepredictionsafteranalyzinganimage.Inotherwords,itmustbeabletoassignaclasstotheimage,orindicatewhetheraspecificelementispresent. Whatcanbedonewithimagerecognition? Withanimagerecognitionsystemorplatform,itispossibletoautomatebusinessprocessesandthusimproveproductivity.Indeed,onceamodelrecognizesanelementonanimage,itcanbeprogrammedtoperformaparticularaction.Severaldifferentusecasesarealreadyinproductionandaredeployedonalargescaleinvariousindustriesandsectors. Forexample,inthetelecommunicationssector,aqualitycontrolautomationsolutionwasdeployed.Infact,fieldtechniciansuseanimagerecognitionsystemtocontrolthequalityoftheirinstallations. Anotherexampleisanintelligentvideosurveillancesystem,basedonimagerecognition,whichisabletoreportanyunusualbehaviororsituationsincarparks. Imagerecognitioncanthereforebedeployedbothintelecommunicationsandvideosurveillance,butalsointheconstructionandpharmaceuticalindustries. SEEMORE OurBlogArticles 07/11/2022 Unit-TpartnerswithDeepomatictoensurethehighestqualityofitsoperationsofgasandelectricitysmartmetersinstallation Readmore 04/7/2022 DeepomaticpartnerswithVECTORSOLUTIONStobringVisualAutomationtoPolishtelecomoperatorsdeployingfiberoptic Readmore 06/13/2022 Webinar:HowVisualAutomationhelpstobuildandmaintainaworld-classfullfibrenetwork? Readmore 02/16/2022 CityFibrepartnerswithDeepomaticfornationwidedeploymentofVisualAutomationTechnology Readmore 04/1/2022 DeepomaticintroducesAssetPerformanceManagementforfieldserviceoperations Readmore 02/25/2022 5tipsforasuccessfulcarbonaccountingprocess Readmore 02/25/2022 Whydoesthetechsectorneedmoretransparency? Readmore 05/6/2021 DeepomaticreceivesnewroundofinvestmentfromSwisscomVenturesandOctaveKlabatofaceacceleratedgrowth Readmore 10/27/2020 NewFeatureRelease:Introducinghierarchicalannotationincomputervisionprojects Readmore 10/22/2020 Fiberopticdeployment:DeepomaticputsitsArtificialIntelligenceplatformattheserviceofthreemajortelecomplayersfortheirfieldoperations Readmore Revolutionizethewayyouwork–onandoffthefield. Curiouswhatvisualautomationcandoforyourbusiness? Let’stalk. Empoweringbusinesswithapplicationsthatseeandunderstandthe physicalworldaswedo. 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