Dr. James McCaffrey of Microsoft Research details the 'Hello World' of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset.

Creating a custom image classification model is challenging, but the existence of neural network libraries like Keras has made it doable. Here's how, with many code samples and a full project download ...

For the MNIST data set, the input images are handwritten digits in the range 0 to 9 [10]. The training and test data sets contain 60,000 and 10,000 labeled images, respectively.

In addition, our results corroborate previous work, which showed that DL models trained on medical images are more vulnerable to misclassifying adversarial images compared with similar DL models ...