Comparative Analysis of SVM and CNN for Hyperspectral Image Classification
https://doi.org/10.31223/X5811M #ComputerEngineering #ComputerSciences #OtherComputerSciences #PhysicalSciencesAndMathematics #ThisPaperPresentsAComparativeAnalysisOfTra-DitionalMachineLearningMethodsAndConvolutionalNeuralNetworks(cnns)ForHyperspectralImageClassification.UtilizingTheIndianPinesDataset #WeExploreTheEfficacyOfPrincipalComponentAnalysis(pca)CombinedWithASupportVectorMachine(svm)ClassifierAgainstADeepLearningApproachInvolvingCnns.OurMethodologyIncludesDimensi #FollowedBySvmClassification #AndTheDesignOfATailoredCnnModelForHyperspectralData.PerformanceMetricsLikeAccuracy #SupportedWithConfusionMatricesAndClassificationMaps #AreEmployedToEvaluateAndCompareTheModels.ResultsIndicateThatCnns #WithTheirAbilityToCaptureSpatialAndSpectralInformation #OutperformTraditionalMethodsInClassificationAccuracyAndRobustness. #HyperspectralImaging #ConvolutionalNeuralNetwork(cnn) #PrincipalComponentAnalysis(pca) #SupportVectorMachine(svm)Classifier
