Computer Vision and Machine Learning Group

Computer vision is the science and technology of machines that see. As a scientific discipline, computer vision is concerned with the theory and technology for building artificial systems that obtain information from images or multi-dimensional data. Machine learning is a subfield of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can teach themselves to grow and change when exposed to new data.

The Computer Vision and Machine Learning group at IMUB studies and develops algorithms in the area of machine learning and computer vision, for example for the task of natural image understanding. Using tools from probability theory, statistics, optimization and deep learning, the members of the group study questions such as: How can a computer identify which objects are visible in an image? or How can we develop semi-supervised learning algorithms?


Simone Balocco

Sergio Escalera

Lluís Garrido

Laura Igual

Eloi Puertas

Oriol Pujol

Petia Radeva

Mireia Ribera

Santi Seguí

Jordi Vitrià

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