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Graduate School of Science and Engineering Information and Computer Science

Intelligent Mechanism Laboratory

Website of Assistant Professor Marie Katsurai 【In Japanese】

Multimedia Understanding, Data Mining, and Visualization

Staff

Masahiro Okuda

OKUDA Masahiro
[Professor]

Acceptable course
Master's degree course
Doctoral degree course

Telephone : 81-774-65-6976
masokuda@mail.doshisha.ac.jp
Office : KC-316
Database of Researchers

Marie Katsurai

KATSURAI Marie
[Associate Professor]

Acceptable course
Master's degree course
Doctoral degree course

Telephone : 81-774-65-7687
mkatsura@mail.doshisha.ac.jp
Office : KC-318
Database of Researchers


Research Topics

Multimedia Understanding: Content, Context, and Sentiment

With the popularity of image-capturing devices and the success of Web 2.0 applications, people have seen a dramatic increase in their ability to collect digital information in various situations and share them on the Web. To develop a system that automatically recognizes the content of multimedia data, we study the complementary use of multi-modal features (e.g., visual features and textual features). We also investigate how to automatically understand images’ semantics, context, and sentiment

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Knowledge Acquisition From Academic Databases

Discovering hot research topics or active research groups from academic databases can contribute to grasping scientific technology trends or to promoting collaborative researches. We, in cooperation with National Institute of Informatics, develop new techniques for analyzing CiNii Articles, the largest academic database in Japan. Specifically, we study the automatic construction of researcher networks based on research topics’ similarities. Visualizing such networks can provide us with new findings about the range of researchers’ interests or changes of research themes over time.

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Research on image restoration methods using convex optimization

Formulate image restoration problems, such as denoising, deblurring, and super-resolution, as convex optimization problems, and restore high-quality images by designing objective functions and regularization terms that preserve image structures and textures.


 Research on hyperspectral image analysis methods

Analyze high-dimensional spectral information obtained from hyperspectral images, extract material-specific features, and develop methods for classification, detection, and visualization of objects or surface properties that are difficult to distinguish using ordinary RGB images.




Keywords

  • Data Mining
  • Multimedia Recognition
  • Image Annotation
  • Scientific Mapping
  • Academic Database
  • Pattern Recognition and Machine Learning