# What are the Receptive, Effective Receptive, and Projective Fields of Neurons in Convolutional Neural Networks?

arXiv: https://arxiv.org/abs/1705.07049 · HTML: https://mlsanity.com/paper/1705.07049/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 May 2017.

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## Abstract (arXiv)

In this work, we explain in detail how receptive fields, effective receptive fields, and projective fields of neurons in different layers, convolution or pooling, of a Convolutional Neural Network (CNN) are calculated. While our focus here is on CNNs, the same operations, but in the reverse order, can be used to calculate these quantities for deconvolutional neural networks. These are important concepts, not only for better understanding and analyzing convolutional and deconvolutional networks, but also for optimizing their performance in real-world applications.