Nice work!

You might want to take a look at the MNIST database (https://en.wikipedia.org/wiki/MNIST_database) which is freely available and commonly used to train neural network. It will also allow you to benchmark your implementation against other algorithms.

On Fri, Dec 6, 2019 at 10:07 AM Murilo via Digitalmars-d-announce <digitalmars-d-announce@puremagic.com> wrote:

Hi everyone. I've spent the last weeks working on a program which
is able to read and understand text from an image file(OCR) by
using a rudimentary neural network after training with a large
amount of images(I made them myself, manually). It even shows a
map of all the parts of the images that have the highest synaptic
weights(warmer colors). It was made purely in D using the arsd
library. Below is the link to it if you wish to take a look. For
now it only understands upper case letters from the English
alphabet. I'll be adding more over time. Cheers.
https://github.com/MuriloMir/Optical-Character-Recognition