Rapid Convolutional Neural Networks for Gram-Stained Image Classification at Inference Time on Mobile Devices: Empirical Study from Transfer Learning to Optimization

Despite the emergence of mobile health and the success of deep learning (DL), deploying production-ready DL models to resource-limited devices remains challenging. Especially, during inference time, the speed of DL models becomes relevant. We aimed to accelerate inference time for Gram-stained analy...

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Detalles Bibliográficos
Autores principales: Kim, Hee E., Maros, Mate E., Siegel, Fabian, Ganslandt, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688012/
https://www.ncbi.nlm.nih.gov/pubmed/36359328
http://dx.doi.org/10.3390/biomedicines10112808

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688012/
https://www.ncbi.nlm.nih.gov/pubmed/36359328
http://dx.doi.org/10.3390/biomedicines10112808

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