FlowCyt: {A} Comparative Study of Deep Learning Approaches for Multi-Class Classification in Flow Cytometry Benchmarking

Bibtex entry :

@techreport { bini.arxiv2024a,
    author = { Lorenzo Bini and Fatemeh Nassajian Mojarrad and Margarita Liarou and Thomas Matthes and St\'ephane Marchand-Maillet },
    title = { FlowCyt: {A} Comparative Study of Deep Learning Approaches for Multi-Class Classification in Flow Cytometry Benchmarking },
    journal = { CoRR },
    volume = { abs/2403.00024 },
    year = { 2024 },
    url = { https://doi.org/10.48550/arXiv.2403.00024 },
    doi = { 10.48550/ARXIV.2403.00024 },
    eprinttype = { arXiv },
    eprint = { 2403.00024 },
    timestamp = { Tue, 02 Apr 2024 16:35:34 +0200 },
    biburl = { https://dblp.org/rec/journals/corr/abs-2403-00024.bib },
    bibsource = { dblp computer science bibliography, https://dblp.org },
}
--

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