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Structural Compression of Convolutional Neural Networks with Applications in Interpretability
Deep convolutional neural networks (CNNs) have been successful in many tasks in machine vision, however, millions of weights in the form of thousands of convolutional filters in CNNs make them difficult for human interpretation or understanding in science. In this article, we introduce a greedy stru...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8427695/ https://www.ncbi.nlm.nih.gov/pubmed/34514381 http://dx.doi.org/10.3389/fdata.2021.704182 |