H{\&}E-adversarial network: a convolutional neural network to learn stain-invariant features through Hematoxylin {\&} Eosin regression

Bibtex entry :

@techreport { marini:arxiv2022,
    author = { Niccol{\`{o}} Marini and Manfredo Atzori and Sebastian Ot{\'{a}}lora and St{\'{e}}phane Marchand{-}Maillet and Henning M{\"{u}}ller },
    title = { H{\&}E-adversarial network: a convolutional neural network to learn stain-invariant features through Hematoxylin {\&} Eosin regression },
    journal = { CoRR },
    volume = { abs/2201.06329 },
    year = { 2022 },
    url = { https://arxiv.org/abs/2201.06329 },
}
--

Keywords: machine learning, information geometry, data mining, Big Data, affective information retrieval (recherche d'information), information visualisation, content-based image and video retrieval (CBIR, CBR, CBVR, CBMR, CBMIR), information mining, classification, multimedia and multimodal information management, semantic web, knowledge base (RDF, OWL, XML, metadata, auto-annotation, description), multimodal information fusion