Semantically Redundant Training Data Removal and Deep Model Classification Performance: A Study with Chest X-rays

Deep learning (DL) has demonstrated its innate capacity to independently learn hierarchical features from complex and multi-dimensional data. A common understanding is that its performance scales up with the amount of training data. Another data attribute is the inherent variety. It follows, therefo...

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Detalles Bibliográficos
Autores principales: Rajaraman, Sivaramakrishnan, Zamzmi, Ghada, Yang, Feng, Liang, Zhaohui, Xue, Zhiyun, Antani, Sameer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cornell University 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659445/
https://www.ncbi.nlm.nih.gov/pubmed/37986725

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659445/
https://www.ncbi.nlm.nih.gov/pubmed/37986725

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