The Maritime University of Szczecin once again boldly embraces the development of the latest digital technologies.
The group of scientists from the MUS Faculty of Navigation started cooperation with Kraków based company Numlabs on the opportunities to use methods of data science and machine learning to implement new solutions in the research of the seabed and in-depth analysis of LIDAR remote sensing data (distance measurement using light beams in the form of pulsed laser imaged on 3D visualizations).
The first part of the specialist training, attended by staff of the newly established Department of Geodesy and Offshore Survey at the Faculty of Navigation, concerned the use of the Python programming language to process geospatial data, including the use of machine learning issues in Big Data. The next step in broadening the competencies of FoN staff will be using libraries collection for the analysis of seabed survey data by applying machine learning techniques.
Both parties are satisfied with the cooperation to date and underline the potential that lies in contacts between the business and academic environments.
The first part of the specialist training, attended by staff of the newly established Department of Geodesy and Offshore Survey at the Faculty of Navigation, concerned the use of the Python programming language to process geospatial data, including the use of machine learning issues in Big Data. The next step in broadening the competencies of FoN staff will be using libraries collection for the analysis of seabed survey data by applying machine learning techniques.
Cooperation between business and science
Numlabs comprises a team of highly specialised analysts, programmers and engineers working on artificial intelligence, machine learning and data analytics technologies. As a business advisor to various industries, Numlabs helps to optimise key decision-making processes by implementing innovative analytical solutions. It also develops tools and systems tailored to customer needs that use AI to analyse images, videos, text or time-series data.Both parties are satisfied with the cooperation to date and underline the potential that lies in contacts between the business and academic environments.