Unsupervised region proposal and supervised patch extraction algorithms for extracting candidate 2D ROIs to train SVM/CNN classifiers, for mass detection in mammograms.
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Updated
May 1, 2020 - Jupyter Notebook
Unsupervised region proposal and supervised patch extraction algorithms for extracting candidate 2D ROIs to train SVM/CNN classifiers, for mass detection in mammograms.
Implementation of various machine learning algorithms from scratch, including Linear Regression, K-Nearest Neighbors, Decision Trees, and K-Means clustering. Also done EDA on data, Implemented LSH, IVF, SLIC algorithms also with evaluation metrics
Implemented the SLIC superpixel algorithm in C++ and image transitions.
Superpixel Clustering using Kmeans in RGBXY and the SLIC algorithm
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