Remember that the functions of location, classification, and analysis are tasks that humans are naturally good at but have been very difficult to perform with traditional rule-based machine vision. Oftentimes in deep learning, these three functions are performed in conjunction to solve a problem. For example, the program may first locate a part in a complex image, then analyze the surface of the part, classifying the types of defects into their respective categories.
Deep learning is not perfect, though it is possible to achieve quality scores of 99.9% (compared to roughly 80% for humans). And oftentimes deep learning alone is not the full answer. However, by combining the expertise of deep learning (location, classification, analysis) with the capabilities of standard rule-based machine vision, we can achieve far more with our vision inspections than previously possible!