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I developed a computer-aided detection system (CAD) using machine learning techniques, including Grayscale, Median filter, High-pass filter, Otsu's Thresholding Technique, and PCA Feature Extraction. The hybrid classifier (SVM-KNN) improved accuracy, and the system identifies brain tumors with 98% accuracy.
Within this repository, the code efficiently collects and preprocesses drawing data. It extracts key parameters like height, width, roundness, elongation, and complexity. These features are then utilized by a K-Nearest Neighbors (KNN) algorithm for precise drawing predictions.
About this Specialization: Take your first step towards a career in software development with this introduction to Java—one of the most in-demand programming languages and the foundation of the Android operating system. Designed for beginners, this Specialization will teach you core programming concepts and equip you to write programs to solve c…