2025
Searching for the Ideal Recipe for Preparing Synthetic Data in the Multi-Object Detection Problem
Staniszewski M, Kempski A, Marczyk M, Socha M, Foszner P, Cebula M, Labus A, Cogiel M, Golba D. Searching for the Ideal Recipe for Preparing Synthetic Data in the Multi-Object Detection Problem. Applied Sciences 2025, 15: 354. DOI: 10.3390/app15010354.Peer-Reviewed Original ResearchSynthetic dataUtilization of synthetic dataSynthetic data generation methodAdvancement of deep learning methodsSynthetic data generation techniquesReal-world datasetsLevel of photorealismDeep learning methodsDetection methodData generation techniquesData generation methodEnhanced detection methodNetwork trainingClassification qualityDetection metricsDetection problemLearning methodsTraining datasetTraining processGeneration methodData quantityGeneration techniqueMulti-objectiveTraining methodsDataset
2021
Distortion Energy for Deep Learning-Based Volumetric Finite Element Mesh Generation for Aortic Valves
Pak D, Liu M, Kim T, Liang L, McKay R, Sun W, Duncan J. Distortion Energy for Deep Learning-Based Volumetric Finite Element Mesh Generation for Aortic Valves. Lecture Notes In Computer Science 2021, 12906: 485-494. DOI: 10.1007/978-3-030-87231-1_47.Peer-Reviewed Original ResearchFinite element analysisVolumetric meshFinite element methodMesh generation techniqueFinite element mesh generationWatertight surface meshesSurface meshElement analysisElement methodStress analysisMeshing techniqueClosure simulationHexahedral elementsGood spatial accuracyDeformation frameworkMesh generationElement qualityOffset operationAccurate generationDeep learningSpatial accuracyDistortion energyMeshModeling strategyGeneration technique
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