The Ohio State University

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  • Pattern Recognition, 874.
    Fundamentals of pattern recognition and machine learning. This is a mostly theoretical course, reviewing the fundamental mathematical tools needed to derive new algorithm in pattern recognition. Derivations are provided for the most known and used techniques as well as those under development. Current research directions are outlined. Applications to vision, cognitive sceinec and bioengineering.


  • Computer Vision, 863.
    Advanced topics in computer vision research. The course surveys a collection of novel ideas currently under study by the research community. The course describes some advanced mathematical models, but emphasis is given to the main ideas. The course discusses a variety of applications including robotics, human-computer interaction, medicine and bio.


  • Image Processing, 707.
    Fundamentals and research directions in image processing: cameras, geometry, calibration, 2D and 3D reconstruction, Fourier transforms, filtering, compression, motion estimation, and applications. The course gives an indepth overview of the mathematical tools needed to successully appliy image processing techniques in the real world. The course includes a nice combination of theory and applications.


  • Computer and Logic Design, 261.


Course information, grades and posteings are available through Carmen.