Image processing: Basics and 3D Reconstruction

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Explores composition, pooling, continuity, denoising, and popular CNN architectures for image segmentation in image processing.

Explores Fourier Transform, frequency filtering, segmentation, and particle size estimation using image analysis techniques.

Discusses edge detection techniques and the evolution of deep learning in neural networks.

Covers the basics of computer vision, focusing on image processing techniques and feature detection.

Explores topology concepts and edge detection in computer vision, highlighting the significance of contours and gradients in image analysis.

Covers practical aspects of using Fiji for everyday tasks in biological imaging.

Covers basic to advanced morphological operations for image analysis workflows.

Explores denoising signals with Gaussian mixture models and EM algorithm, EMG signal analysis, and image segmentation using Markovian models.