Understanding Image Normalization in CNNs
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2025
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| _version_ | 1866901521415798784 |
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| author | Laurent Perrinet |
| author_facet | Laurent Perrinet |
| contents | <p>[](https://doi.org/10.5281/zenodo.14602370)</p> <p>#ConvolutionalNeuralNetworks (#CNNs in short) are immensely useful for many #imageProcessing tasks and much more... Yet you sometimes encounter some bits of code </p> <p>Have you ever wondered about the origins of the values for image normalization in #imagenet ?</p> <p><br>* Mean: `[0.485, 0.456, 0.406]` (for R, G and B channels respectively)<br>* Std: `[0.229, 0.224, 0.225]`</p> <p>Strangest to me is the need for a three-digits precision. Here, after finding the origin of these numbers for MNIST and ImageNet, I am testing if that precision is really important : guess what, it is not !</p> <p>* https://laurentperrinet.github.io/sciblog/posts/2024-12-09-normalizing-images-in-convolutional-neural-networks.html<br>* https://nbviewer.org/github/laurentperrinet/2024-12-09-normalizing-images-in-convolutional-neural-networks/blob/main/2024-12-09-normalizing-images-in-convolutional-neural-networks.ipynb</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_14602370 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Understanding Image Normalization in CNNs Laurent Perrinet Deep Learning CNN normalization Image processing Computer vision <p>[](https://doi.org/10.5281/zenodo.14602370)</p> <p>#ConvolutionalNeuralNetworks (#CNNs in short) are immensely useful for many #imageProcessing tasks and much more... Yet you sometimes encounter some bits of code </p> <p>Have you ever wondered about the origins of the values for image normalization in #imagenet ?</p> <p><br>* Mean: `[0.485, 0.456, 0.406]` (for R, G and B channels respectively)<br>* Std: `[0.229, 0.224, 0.225]`</p> <p>Strangest to me is the need for a three-digits precision. Here, after finding the origin of these numbers for MNIST and ImageNet, I am testing if that precision is really important : guess what, it is not !</p> <p>* https://laurentperrinet.github.io/sciblog/posts/2024-12-09-normalizing-images-in-convolutional-neural-networks.html<br>* https://nbviewer.org/github/laurentperrinet/2024-12-09-normalizing-images-in-convolutional-neural-networks/blob/main/2024-12-09-normalizing-images-in-convolutional-neural-networks.ipynb</p> |
| title | Understanding Image Normalization in CNNs |
| topic | Deep Learning CNN normalization Image processing Computer vision |
| url | https://doi.org/10.5281/zenodo.14602370 |