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    Exploiting multiview properties in semi-supervised video classification

    , Article 2012 6th International Symposium on Telecommunications, IST 2012 ; 2012 , Pages 837-842 ; 9781467320733 (ISBN) Karimian, M ; Tavassolipour, M ; Kasaei, S ; Sharif University of Technology
    Abstract
    In large databases, availability of labeled training data is mostly prohibitive in classification. Semi-supervised algorithms are employed to tackle the lack of labeled training data problem. Video databases are the epitome for such a scenario; that is why semi-supervised learning has found its niche in it. Graph-based methods are a promising platform for semi-supervised video classification. Based on the multiview characteristic of video data, different features have been proposed (such as SIFT, STIP and MFCC) which can be utilized to build a graph. In this paper, we have proposed a new classification method which fuses the results of manifold regularization over different graphs. Our... 

    Automated analysis of karyotype images

    , Article Journal of Bioinformatics and Computational Biology ; Volume 20, Issue 3 , 2022 ; 02197200 (ISSN) Khazaei, E ; Emrany, A ; Tavassolipour, M ; Mahjoubi, F ; Ebrahimi, A ; Motahari, S. A ; Sharif University of Technology
    World Scientific  2022
    Abstract
    Karyotype is a genetic test that is used for detection of chromosomal defects. In a karyotype test, an image is captured from chromosomes during the cell division. The captured images are then analyzed by cytogeneticists in order to detect possible chromosomal defects. In this paper, we have proposed an automated pipeline for analysis of karyotype images. There are three main steps for karyotype image analysis: image enhancement, image segmentation and chromosome classification. In this paper, we have proposed a novel chromosome segmentation algorithm to decompose overlapped chromosomes. We have also proposed a CNN-based classifier which outperforms all the existing classifiers. Our...