ML Anthology

Computing Receptive Fields of Convolutional Neural Networks

André Araujo, Wade Norris, Jack Sim
Distill 2019
doi:10.23915/distill.00021 /distill/2019/araujo2019distill-computing/

Abstract

Distill articles are interactive publications and do not include traditional abstracts. This summary was written for the ML Anthology. Derives closed-form expressions for computing receptive fields in convolutional neural networks and extends these methods to modern architectures with multiple computational paths, such as ResNets and Inception networks.

Distill Code Semantic Scholar

Cite

Text

Araujo et al. "Computing Receptive Fields of Convolutional Neural Networks." Distill, 2019. doi:10.23915/distill.00021

Markdown

[Araujo et al. "Computing Receptive Fields of Convolutional Neural Networks." Distill, 2019.](https://mlanthology.org/distill/2019/araujo2019distill-computing/) doi:10.23915/distill.00021

BibTeX

@article{araujo2019distill-computing,
  title     = {{Computing Receptive Fields of Convolutional Neural Networks}},
  author    = {Araujo, André and Norris, Wade and Sim, Jack},
  journal   = {Distill},
  year      = {2019},
  doi       = {10.23915/distill.00021},
  url       = {https://mlanthology.org/distill/2019/araujo2019distill-computing/}
}