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  1. After reading the first three chapters:
    • list the main parts/components/structures of the model.
    • Is their creation dependent on other components?
  2. Thinking about the scripts:
    • What is the main reason (the biggest advantage) of using scripts? What kind of information does it bring? (Hint: page 2, page 8)
    • The authors don't get the “knowledge” of scripts straightforwardly. How is that “knowledge” represented in the model and which (two) ways are used to get it?
  3. In the last paragraph of Section 3, a method is described that enhances the robustness of the model (binarization of all association weights <latex>w^z_i</latex>). Answer one of the following questions (choose one):
    • Why does it work? (⇒ Why should it work best?)
    • Do you have any idea how to do it differently?
  4. Which tools enhanced the Attribute recognition and Composite activity classification tasks “the most”? Try to answer why.

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