We have explored how deep learning can understand text. Now, let's explore how deep learning models can see. In 2010, the first ImageNet Large Scale Visual Recognition Challenge was held. The task was to create a classification model that solved the ambitious task of recognizing an object in an image. In total, there are around 22,000 categories to choose from. The dataset contains over 14 million labeled images. If someone sat and chose the top 5 objects for each image, they would have an error rate of around 5%.
In 2015, a deep neural network surpassed human performance on ImageNet. Since then, many computer vision algorithms have been rendered obsolete. Deep learning allows us not only to classify images, but ...
