ABSTRACT. In this keynote speech, I will discuss how bioimage informatics is advancing our understanding of the detailed structures and processes inside cells and organisms, which are crucial for understanding the basic functions of life. I will show how combining this knowledge with healthcare data can help us predict diseases and monitor recovery, particularly in cancer treatment. I will also highlight our groundbreaking work to create the first atlas of human cell division and discuss the exciting potential of developing similar resources for model organisms. This talk will highlight the essential links between fundamental research, practical applications, and real-world solutions, demonstrating how computer-driven methods can bring together various scientific fields to enhance our knowledge and foster innovation in health and biology.

ABSTRACT. We employ several types of remote sensing data such as multispectral, hyperspectral, radar and point cloud data for various object extraction and/or modelling, e.g., buildings, powerline and landcover classification.

ABSTRACT. The availability of huge datasets has frequently been praised as a prerequisite for creating successful models in the quickly changing field of machine learning. In actuality, though, a lot of real-world applications are limited by data. The difficulties and possibilities that come with working with limited datasets in machine learning will be covered in detail in this talk.