FH goes Machine Learning Prague 2024

Following Fabian Kovac's keynote speech last year, a delegation consisting of Alexander Buchelt, Oliver Eigner, Sebastian Eresheim and Fabian Kovac from the Data Intelligence research group at the Institute of IT Security Research attended Machine Learning Prague again this year.

Machine Learning Prague is Europe's largest conference on machine learning, AI and deep learning applications and inspires over 1000 participants from all over the world with business and research for 3 days every year.

Workshop "Unlocking the Power of Active Learning: A Hands-on Exploration"

In the ever-evolving landscape of artificial intelligence and machine learning, staying on top of the latest developments is not just an advantage, but a necessity. Active learning has emerged as a powerful technique that has the potential to revolutionize the way machine learning models work. In this hands-on workshop, Fabian Kovac and Oliver Eigner provided participants with a comprehensive understanding of its relevance, benefits and practical applications.

This workshop by Oliver Eigner and Fabian Kovac is a hands-on, immersive experience that provides a solid foundation for the theoretical principles and ensures that the core concepts are made clear to participants.
Participants had the opportunity to apply active learning techniques to real-world datasets, gain hands-on experience in selecting informative data points, train models and observe the impact on model performance. In addition, best practices and pitfalls to avoid when implementing active learning in real-world applications were presented.

Poster "Navigating Nature's Labyrinth"

The dynamic landscape of machine learning and artificial intelligence (AI) has experienced rapid and transformative growth in recent years, ushering in an era where the exploration of its potential applications spans a multitude of domains. The need to harness the capabilities of AI has transcended traditional boundaries and requires an in-depth exploration of its potential impact, particularly with regard to combating climate change through the preservation of carbon sequestering forests.

Given their crucial role in combating climate change, there is an urgent need to protect the health and efficiency of these ecosystems. Currently, the manual execution of forestry tasks remains a labor-intensive and risky endeavor, highlighting the forestry sector as fertile ground for exploring the positive impact of artificial intelligence on society.

The main goal of this research is to enable drones to navigate autonomously through forests - a crucial prerequisite for the effective implementation of AI in forestry. Therefore, this project prioritizes drones as ideal platforms for the integration of artificial intelligence in forestry, as they are able to navigate even the most difficult terrain.

"It is a pleasure that our students and employees take on new key roles in ML Prague every year and thus actively drive digitalization and digital transformation," says Marlies Temper, Head of the Bachelor's degree program Data Science and Business Analytics and the Master's degree program Data Intelligence.