Lectures related to Image Processing II: Multiresolution Analysis and Wavelet Transform

Hypothesis Testing and Non-Parametric Regression

Covers worked examples on hypothesis testing and non-parametric regression.

Covers feature extraction, clustering, and classification methods for high-dimensional datasets and behavioral analysis using PCA, t-SNE, k-means, GMM, and various classification algorithms.

Image Processing II: B-spline Properties and Gradient Operators

Explores B-spline properties, gradient operators, interpolation, and differentiation filters in image processing.

Generalization Error

Discusses mutual information, data processing inequality, and properties related to leakage in discrete systems.

Non-parametric Regression: Smoothing Techniques

Explores non-parametric regression techniques, including splines, bias-variance tradeoff, orthogonal functions, wavelets, and modulation estimators.

Image Processing I: Segmentation and Thresholding

Explores image segmentation, thresholding techniques, texture segmentation, and connected-component labeling in image processing.