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Computer Vision and Biosystem Signal Processing

In recent years, computer vision and machine learning have gained popularity at a near exponential pace due to the impressive achievement on real-world problems. In our group, we research techniques and devise methodologies for acquiring, processing and analyzing information in image data and other types for data.

Researching these methodologies lead to concrete solutions to real-world problems for facilitating analysis and decision making in industry and research. We devise methodologies for acquiring domain specific dataset. We research computer vision and machine learning methods in e.g. Convolutional Neural Networks, Generative Adversarial Networks and Deep Reinforcement Learning.

Applications include precision agriculture, weed and crop classification and analysis and autonomous systems. Our ambition is to advance computer vision and machine learning technology and facilitate the adoption of state-of-the-art solutions in our society through industrial and academic collaboration.

Our research is primary founded by Innovation Fund Denmark, GUDP Denmark, public consultancy funds, industrial and private founding.