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Aggelos K. Katsaggelos
Researcher at Northwestern University
Publications - 999
Citations - 28918
Aggelos K. Katsaggelos is an academic researcher from Northwestern University. The author has contributed to research in topics: Image restoration & Image processing. The author has an hindex of 76, co-authored 946 publications receiving 26196 citations. Previous affiliations of Aggelos K. Katsaggelos include University of Stavanger & Delft University of Technology.
Papers
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Proceedings Article
Iterative method for restoring noisy blurred images.
TL;DR: In this paper, the authors proposed a new iterative image restoration method which is capable of restoring noisy blurred images by incorporating a priori knowledge about the image and noise statistics into the iterative procedure.
Proceedings ArticleDOI
Feature space video stream consistency estimation for dynamic stream weighting in audio-visual speech recognition
TL;DR: This work inferring the "consistency" between the audio and visual information and leveraging the existing audio reliability metrics to create a video reliability metric that competes with the audio-only reliability metric based systems and shows promise to consistently outperform.
Proceedings ArticleDOI
Regularized restoration of partial-response distortions in sporadically degraded images
D.L. Tull,Aggelos K. Katsaggelos +1 more
TL;DR: A regularized iterative restoration of sporadically degraded images resulting in K restored images is proposed and demonstrates a promising (object based) image restoration approach for video editing applications.
Journal ArticleDOI
Teaching citizen scientists to categorize glitches using machine learning guided training
Corey Brian Jackson,Corey Brian Jackson,Carsten Østerlund,Kevin Crowston,Mahboobeh Harandi,Sarah Allen,Sara Bahaadini,S. B. Coughlin,Vicky Kalogera,Aggelos K. Katsaggelos,Shane L. Larson,Neda Rohani,J. R. Smith,Laura Trouille,Michael Zevin +14 more
TL;DR: A training regime combining scaffolded instruction and machine learning to select learning materials and gradually introduces new materials to individuals as their competences improve is designed and tested and suggests that MLGT is an effective pedagogical approach for training volunteers in categorization tasks and increases volunteers’ motivation.
Proceedings ArticleDOI
Spatially adaptive image restoration for autoradiography
TL;DR: The model involves a point spread function (PSF) due to the radiated pattern of emitted photons combined with a signal-dependent noise sourceDue to the granularity of x-ray recording film to improve the resolution of autoradiographic images.