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Enhanced Feature Vector Calculation Methods Review

This project focuses on developing and comparing four different methods for computing feature vectors using HKS, analyzing their advantages and disadvantages, with a special emphasis on ROC curve analysis.

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Enhanced Feature Vector Calculation Methods Review

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  1. INFOMR Project Dafne van Kuppevelt ● VikramDoshi● SeçkinSavaşçı Development Review

  2. Feature Vector Calculation • Compute feature vector using HKS • 4 different Methods

  3. First Method • Compute • Use logarithmically scale over a time interval [-4, 2] • Disadvantage: t’s are not fitted to the object

  4. Second Method • Compute by uniformly sampling 100 points in the logarithmically scale over the time interval [tmintmax]

  5. Second Method • (ROC Cuve)

  6. Second Method • Gives much better results • HKSSumt remains almost unchanged for t > tmax as it is mainly determined by the eigenvector 𝛷2.

  7. Third Method • Use only 300 eigenvectors and eigenvalues • Compute by uniformly sampling 100 points in the logarithmically scale over the time interval [tmintmax] • ,

  8. Third Method • (ROC Curve) • Complexity much lower!

  9. Fourth Method

  10. Performance Analysis • ROC curve

  11. Performance Analysis • Precision/Recall graph

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