Title |
Lightweight Visual Transformers Outperform Convolutional Neural Networks for Gram-Stained Image Classification: An Empirical Study / Hee E. Kim, Mate E. Maros, Thomas Miethke, Maximilian Kittel, Fabian Siegel, Thomas Ganslandt |
|---|---|
Involved |
Hee Eun Kim (Verfasser)
Máté E. Maros (Verfasser) Thomas Miethke (Verfasser) Maximilian Kittel (Verfasser) |
Published |
Erlangen: Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) |
Extent |
Online-Ressource |
Language |
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Country |
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Topic |
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Subject |
Gram-stain analysis
classification deep learning quantization
vision transformer
convolutional neural network |
DDC notation |
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Persistent identifier |
urn:nbn:de:bvb:29-opus4-228316 (URN) |
Further information |
In: Biomedicines 11.5 (2023): 1333. <https://www.mdpi.com/2227-9059/11/5/1333> |
Record ID |
1289237913 |
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