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EmbedFormer: Embedded Depth-Wise Convolution Layer for Token Mixing
Visual Transformers (ViTs) have shown impressive performance due to their powerful coding ability to catch spatial and channel information. MetaFormer gives us a general architecture of transformers consisting of a token mixer and a channel mixer through which we can generally understand how transfo...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9782848/ https://www.ncbi.nlm.nih.gov/pubmed/36560222 http://dx.doi.org/10.3390/s22249854 |