EXSCLAIM!: Harnessing materials science literature for self-labeled microscopy datasets

This work introduces the EXSCLAIM! toolkit for the automatic extraction, separation, and caption-based natural language annotation of images from scientific literature. EXSCLAIM! is used to show how rule-based natural language processing and image recognition can be leveraged to construct an electro...

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Detalles Bibliográficos
Autores principales: Schwenker, Eric, Jiang, Weixin, Spreadbury, Trevor, Ferrier, Nicola, Cossairt, Oliver, Chan, Maria K.Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10682750/
https://www.ncbi.nlm.nih.gov/pubmed/38035197
http://dx.doi.org/10.1016/j.patter.2023.100843

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10682750/
https://www.ncbi.nlm.nih.gov/pubmed/38035197
http://dx.doi.org/10.1016/j.patter.2023.100843

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