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image-preprocessing

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The binary classification problem focused on first IEEE Image forensics challenge-phase 1, to predict the given image is pristine or manipulated/edited/fake. Comparing CNN & Transfer Learning models for the problem and boosting the performance by feature extraction

  • Updated Aug 10, 2019
  • Jupyter Notebook

Face Recognition/Detection (image/video) using skin tone threshold algorithm, haar cascade for face detection and LBPH for face recognition. It also implements the concept of multithreaded server with multiple clients.

  • Updated Jul 27, 2020
  • Python

This DR detection methodology has six steps: preprocessing, segmentation of blood vessels, segmentation of OD, detection of MAs and hemorrhages, feature extraction and classification. For segmentation of blood vessels BCDU-Net is used. For OD segmentation, U-Net model is used. MAs and hemorrhages are extracted using Otsu thresholding technique. …

  • Updated Oct 2, 2020
  • Jupyter Notebook

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