Anders Hast
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.
His recent research has focused on computer vision, image processing and machine learning techniques, for a wide range of applications, such as hand written text recognition and face recognition. In this project he is focusing on age estimation from facial photographs.
Professor Anders Hast, Information technology, Department of Information Technology, Uppsala Universitet, Sweden
Selection of publications
A. Hast. Yijie Zhou, Congting Lai and Ivar Blohm. Analysis of Age Invariant Face Recognition Efficiency using Face Feature Vectors.
ROBOVIS 2024, held in conjunction with ICAART 2024, ICPRAM 2024 and VISIGRAPP 2024. Rome, Italy. pp 47-65, 2024.
A. Hast. Age-Invariant Face Recognition using Face Feature Vectors and Embedded Prototype Subspace Classifiers. 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.
A. Hast. Sex Classification of Face Images using Embedded Prototype Subspace Classifiers. 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.
A. Hast. Consensus Ranking for Efficient Face Image Retrieval: A Novel Method for Maximising Precision and Recall. In: Foresti, G.L., Fusiello, A., Hancock, E. (eds) Image Analysis and Processing – ICIAP 2023. ICIAP 2023. Lecture Notes in Computer Science, vol 14233. Springer, Cham. Presented at the 22nd International Conference on Image Analysis and Processing. Udine, Italy. pp. 159-170. 2023.
A. Hast. Magnitude of Semicircle Tiles in Fourier-space - A Handcrafted Feature Descriptor for Word Recognition using Embedded Prototype Subspace Classifiers.
Journal of WSCG, ISSN 1213-6972, Vol.30. No.1-2, DOI: 10.24132/JWSCG.2022.10, Journal, pp. 82-90. 2022
A. Hast, E. Vats. Word Recognition using Embedded Prototype Subspace Classifiers on a new Imbalanced Dataset. Journal of WSCG, Vol.29, No.1-2, ISSN 1213-6972, Journal. pp. 39-47. 2021
A. Hast, M. Lind.Ensembles and Cascading of Embedded Prototype Subspace Classifiers. Journal of WSCG, ISSN 1213-6972, Vol. 28, No. 1-2, Journal. pp. 89-95. 2020.
S. Chanda, A. Chakrapani Gv, A.Brun, A. Hast, U. Pal and D. Doermann. Face Recognition - A One-Shot Learning Perspective. 15th IEEE Conference on Signal Image Technology and Internet based Systems, Sorrento, Italy, Full paper. pp. 113-119, 2019.
S. Chanda, P. K. Prasad, A. Hast, A. Brun, L. Mårtensson and U. Pal. Finding Logo and Seal in Historical Document Images - An Object Detection based Approach.The 5th Asian Conference on Pattern Recognition (ACPR 2019), Poster 2019.