FCAI SIG
AI for computer vision
Coordination: Professor Moncef Gabbouj (University of Tampere), Professor Guoying Zhao (University of Oulu), Professor Juho Kannala (Aalto University)
One of the core computer vision areas, namely, object recognition with large scale image datasets, was accredited largely for the recent advances in machine learning especially deep learning. Object classification with deep learning and large scale data is arguably what reignited the field of artificial neural networks and triggered a revolution in artificial intelligence. Since then, deep learning techniques shine in a broad range of areas such as computer vision, speech recognition and language translation.
Nowadays, artificial intelligence has spread over almost all fields of science and technology. Yet, computer vision remains in the heart of these advances when it comes to visual data analysis, offering the biggest big data and enabling advanced AI solutions to be developed focusing on the various problems and applications of computer vision.
Computer vision research in Finland is distributed in many research organizations with a large concentration at the University of Oulu. FCAI SIG AI for computer vision (CVAI) coordinates research activities using and developing AI tools for computer vision under FCAI umbrella for more efficient cooperation and synergy between the research organizations in Finland.
Objectives
FCAI SIG AI for computer vision aims to bring together experts and research groups in different research organizations in Finland to exchange ideas and collaborate towards a more coordinated and efficient contributions to solving the main challenges in the field for the benefit of the research organizations, the industry and the society at large.
Activities
Organize some workshops and seminars to support collaboration among research groups and with industry;
Share information regarding projects, funding, education, positions, etc;
Researcher exchanges between CV groups
Activities with Pattern Recognition Society of Finland
Research themes
Fundamental feature representation
Visual information retrieval
Affective computing from visual analysis
3D vision
Medical and biomedical image analysis
Autonomous systems
Learning in vision
Empathic building
Materials sciences
Industrial applications of CV
Bio-marine monitoring
Camera imaging
Remote sensing
Safely, security and privacy
Main challenges
The main challenges encountered in the field of AI for CV include
Energy efficient algorithms
Edge computing solutions
Hardware accelerators
Algorithm–hardware codesign
Learning with less labels
Efficient feature representation for small scale and imbalanced data
People:
Liu Li, UO
Janne Heikkilä, UO
Matti Pietikäinen, UO
Guoying Zhao, UO
Petri Myllymäki, UH
Paavo Nevalainen, UTU
Jukka Heikkonen, UTU
Esa Rahtu, TAU
Ville Kyrki, Aalto
Hannu Karvonen, VTT
Otto Korkalo, VTT
Jani Boutellier, UV
Arto Klami, UH
Markus Koskela, CSC
Juho Kannala, Aalto
Patrik Floreen, UH
Jorma Laaksonen, Aalto
Miguel Bordallo Lopez, VTT
Heikki Huttunen, TAU
Lasse Lensu, LUT
Heikki Kälviäinen, LUT
Pekka Pöyry, TAMK