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- After reading the first three chapters:
- list the main parts/components/structures of the model.
- Is their creation dependent on other components?
- Thinking about the scripts (recipes):
- 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?
- 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?
- Which tools enhanced the Attribute recognition and Composite activity classification tasks “the most”? Try to answer why.