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Multi-Media Data Mining

Content of the Lecture

  • models of information retrieval
  • performance evaluation and competitions
  • query based retrieval, nearest neighbors, hash algorithms
  • topic models and vector space models
  • text categorization, analysis, tagging, parsing
  • content based image and video retrieval
  • image retrieval based on color, texture, and shape
  • visual bag of words model
  • automatic annotation and categorization
  • generative and discriminative methods
  • deep learning by convolutional neural networks
  • applications in consumer imaging, forensics, and copyright detection, visual sentiment analysis, emotion detection

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