The term Big Data has been the great technological driver that has revolutionised the business environment. Companies have seen how digital transformation has evolved their environment. The demand for machine vision systems has been increasing in order to handle the large amount of data to be digitised. This is a widespread change that has affected all sectors, as almost all activities can benefit from intelligent and automated data analysis.

One of the keys to artificial intelligence is the evolution it can have through learning. It is becoming more and more common to ask machines to learn on their own, we need machines to be able to self-program themselves and to learn by their own experience. In this post, we tell you everything you need to know about Deep Learning and what machine learning is like.

Machine Learning

The discipline known as Machine Learning is about machines learning from their own experience. This has led Internet giants to offer cloud services and build their applications on the basis of the data they ingest.

The learning algorithm is simpler than we think. If you look closely, you will see that it learns just like we did when we were little. In artificial systems, as with children, behaviours that are rewarded increase in occurrence, while those that are punished tend to disappear.

At present, it is the training constraints or limitations of algorithms that, to a large extent, limit their power to learn effectively. In the field of artificial vision, for example, in order for algorithms to learn to detect objects in images automatically, they must first be trained on a set of labelled images.

How does Deep Learning approach human perception?

In the future, it is possible that machine learning will move towards unsupervised learning. Algorithms are able to learn without prior human intervention, drawing their own conclusions about the data obtained. There are companies that focus entirely on unsupervised machine learning approaches that process hundreds of pieces of data to build structured representations.

The discipline of machine learning, is experiencing a moment of great splendor thanks to its application in the world of Big Data and IoT. Advances and improvements in more traditional algorithms continue to emerge, from classifier ensembles to Deep Learning. The latter is currently very popular for its ability to increasingly approach human perceptual power.

Deep Learning at i-mas

At i-mas, we specialize in developing specialized machinery to automate processes, from mechanical design and manufacturing to assembly and commissioning. All our equipment includes Deep Learning technology, allowing us to provide tailored solutions that meet our clients’ needs.

One of the most striking projects we have developed at i-mas, is a machine for container identification using Deep Learning. Its goal is to identify the type of container, considering that there are 9 different options, with an accuracy rate of 99.99%. A Deep Learning model with redundancy was implemented to increase the accuracy percentage.

Do you want to learn more? In this link, you will find all the information about our engineering department and its services.