This is an important part of my contribution to the field of AI. An earlier blog post, has been updated with new information about this project. Several improvements have been done, which show how to make ensembles and creating efficient feature vectors using the Fourier Transform.

New Papers

  • Age-Invariant Face Recognition using Face Feature Vectors and Embedded Prototype Subspace Classifiers.
    A. Hast.
    Advanced Concepts for Intelligent Vision Systems. In: Blanc-Talon, J., Delmas, P., Philips, W., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2023. Lecture Notes in Computer Science, vol 14124. Springer, Cham. . Presented at ACIVS2023, Kumamoto  Japan, Accepted full paper.  pp 88-99. 2023. pdf
  • Sex Classification of Face Images using Embedded Prototype Subspace Classifiers.
    A. Hast
    Proceedings of the 31th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision WSCG 2023, Plzen, Czech Republic, May 15 – 19. Full paper. pp. 43-52. 2023. pdf
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Published by Anders

Anders Hast received a PhD in Computerised Image processing at Uppsala university in 2004. In 2011 he spent one year at IIT, CNR, Pisa in Italy as an ERCIM fellow and after that he received a full time position as associate professor and in 2019 he became professor in image processing, both at Uppsala University. He has been affiliated with UPPMAX super computer centre where he worked as an application expert in Scientific Visualisation and later in the field of digital humanities together with the Centre for digital humanities in Uppsala. His recent research has focused on image processing and computer vision, for applications in microscopy, aerial photography, object recognition and especially hand written text recognition and face recognition.

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