What is Deep Learning?
Deep Learning is a set of specific algorithms within Machine Learning that provide these machines with the ability to learn by themselves from example. It is based on artificial neuronal networks, attempting to come close to human perception.
Advantages of Deep Learning over Traditional Artificial Vision
• Difficult-to-resolve applications. Resolves complex inspection, classification, and very difficult location applications with classic rule-based algorithms.
• Easier to configure. The applications are configured quickly, accelerating proof of concept and development.
• Does not require software development. Adapts quickly to new models without the need to reprogram its main algorithms.
• Tolerates defect variations. They combine the flexibility and the application of logical criteria of human vision with the security and speed of an artificial vision system.
When to implement Deep Learning?
The choice between traditional artificial vision and Deep Learning depends on:
• Type of application
• Amount of data being processed
• Processing capacities.
Image analysis based on Deep Learning and traditional artificial vision are complementary technologies, with overlapping capacities and different areas where each one stands out. Vision applications can involve both technologies.
