Litcius/Paper detail

S3-VAE: A novel Supervised-Source-Separation Variational AutoEncoder algorithm to discriminate tumor cell lines in time-lapse microscopy images

Paola Casti, S. Cardarelli, Maria Colomba Comes, Michele D’Orazio, Joanna Filippi, Gianni Antonelli, Arianna Mencattini, C. Di Natale, Eugenio Martinelli

2023Expert Systems with Applications19 citationsDOI

Topics & Concepts

AutoencoderComputer scienceArtificial intelligencePattern recognition (psychology)Benchmark (surveying)Pipeline (software)CovarianceDeep learningAlgorithmMathematicsStatisticsGeodesyProgramming languageGeographyCell Image Analysis TechniquesAI in cancer detectionGenerative Adversarial Networks and Image Synthesis
S3-VAE: A novel Supervised-Source-Separation Variational AutoEncoder algorithm to discriminate tumor cell lines in time-lapse microscopy images | Litcius