In Artificial Intelligence, Machine Learning technologies allow us to define algorithms and information technology systems with the capacity to improve their performance by learning from experience. Whether we are discussing supervised learning with annotated data or semi-supervised or even unsupervised learning –without annotations or prior classifications–, or if we use techniques such as Reinforcement Learning or even Deep Learning with deep neuronal networks, our team works on how to apply these techniques to resolve real problems in businesses.
A Common Technological Approach, Different Sectors
Thanks to the current capacity for the generation, storage and transmission of Big Data, and with new Machine Learning algorithms such as Deep Learning, at Vicomtech we have successfully applied disruptive solutions in multiple sectors, such as Industry, Oil and Gas, medicine, transport, cybersecurity, energy, surveillance of critical infrastructures, services, communication and language, Internet and Media, etc.
Machine Learning Enriches Other Key Technologies
Machine Learning technologies have a direct relationship and give an enormous boost to other fundamental technologies at Vicomtech. For example, they are applied in Computer Vision for problems such as the classification of industrial defects, the prediction of dangerous situations in autonomous driving and analysis of cancer images. They are also applied in Data Intelligence to extract valuable information and findings, such as predictions based on data from machinery and industrial production sensors. Or, for example, in Speech, Dialogue and Natural Language Processing, they allow the improvement of transcription and translation systems at previously unknown levels. Machine Learning is an enabler in multiple technologies and sectors.
A couple of examples
A couple of examples will help demonstrate the applicability of Machine Learning. We have helped a large electronics company to develop Augmented Reality stations so that their operators can assemble tens of thousands of electronic components with a system which automatically learns from a few examples. We have provided a world leader in the automotive sector with a system supported by Machine Learning for the semi-automatic annotation of huge amounts of video to prepare its autonomous driving systems. We have helped a continuous process industry predict and anticipate faults in their production, based on data from their sensors and control systems, with very significant savings. These are just a few examples among many showing the relevance and applicability of Machine Learning.
- Noteworthy Projects
A novel method for error analysis in radiation thermometry with application to industrial furnaces
Making the most of comparable corpora in Neural Machine Translation: a case study
Language Resources and Evaluation
Photometric Stereo-Based Defect Detection System for Steel Components Manufacturing Using a Deep Segmentation Network
ArchABM: An agent-based simulator of human interaction with the built environment. CO2 and viral load analysis for indoor air quality
Building and Environment
The SHAPES Smart Mirror Approach for Independent Living, Healthy and Active Ageing
Provides society with safe and healthy environments in areas of daily life for citizens, public buildings, hospitals, schools and other places of daily use
The project focused on developing new epidemiological methodologies and tools for analysis and decision making during the COVID19 pandemic
It develops cognitive robotic platforms based on a modular approach capable of adapting to virtually any industrial scenario by applying agile manufacturing principles.
Development and use of the latest technologies for comprehensive omics analysis and AI in data integration, moving towards the identification of biological fingerprints (biomarkers) and personalised or precision medicine in the Basque Country
Looking for support for your next project? Contact us, we are looking forward to helping you.