When you need your application to find and name things in an image, you need to build a deep neural network for object detection. The visual field is very complex, and a camera for still images and video captures frames with many, many objects in them. Object detection is used in manufacturing for process automation in production lines; autonomous vehicles sensing pedestrians, other cars, the road, and signs, for example; and, of course, facial recognition. Computer vision solutions based on machine learning and deep learning require you, the Data Scientist, to build, train, and evaluate models that can differentiate one object from another and then accurately classify those detected objects.
As you've seen in other projects we've worked on, CNNs are very powerful models for image data. We need to look at expansions on the basic architecture...
