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LdsConv: Learned Depthwise Separable Convolutions by Group Pruning
Standard convolutional filters usually capture unnecessary overlap of features resulting in a waste of computational cost. In this paper, we aim to solve this problem by proposing a novel Learned Depthwise Separable Convolution (LdsConv) operation that is smart but has a strong capacity for learning...
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| Gepubliceerd in: | Sensors (Basel) |
|---|---|
| Hoofdauteurs: | , , , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
MDPI
2020
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7435949/ https://ncbi.nlm.nih.gov/pubmed/32759800 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s20154349 |
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