Update README.md

README.md

@@ -84,6 +84,9 @@ Although these examples require deeper understanding about neural networks, they
 * [Gradient Ascent](https://github.com/joaopauloschuler/neural-api/tree/master/examples/GradientAscent) - Visualizing patterns from inner neurons in image classification <p><img src="https://github.com/joaopauloschuler/neural-api/blob/master/docs/gradientascent3layer.jpg" height="130"></img></p>
 * [Artificial Art](https://github.com/joaopauloschuler/neural-api/tree/master/examples/VisualGAN) - Let a neural network produce art via a generative adversarial network <p><img src="https://github.com/joaopauloschuler/neural-api/blob/master/docs/art1.png" height="130"></img></p>
 * [Super Resolution](https://github.com/joaopauloschuler/neural-api/tree/master/examples/SuperResolution) - A neural network learns how to increase image resolution<p><img src="examples/SuperResolution/results/building_result.png"></img></p>
+in maXbox and Lazarus:
+![lazarus_maxbox_superresolution3](https://user-images.githubusercontent.com/3393121/224761196-9eb8ff9f-3c84-4f61-9c9e-a9aee5b8b709.png)
+
 * [Autoencoder](https://github.com/joaopauloschuler/neural-api/tree/master/examples/VisualAutoencoder) - Shows an autoencoder built with hyperbolic tangents and trained with [Tiny ImageNet 200](https://tiny-imagenet.herokuapp.com/). <p><img src="docs/autoencoder_small.png"></img></p>
 
 There are also some [older code examples](https://sourceforge.net/p/cai/svncode/HEAD/tree/trunk/lazarus/experiments/) that you can look at.