Object co-segmentation

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Related lectures (31)

Image processing: Basics and 3D Reconstruction

Explores image processing in 2D and 3D, covering ideal imaging conditions, histogram analysis, tools, 3D reconstruction steps, and visualization.

Image Processing I: Local Normalization and Morphological Operators

Introduces local normalization and morphological operators for shape analysis in image processing.

A Localization Tale: Practical Course by BIOP

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

K-Means Clustering: Basics and Applications

Introduces K-Means Clustering, a simple yet effective algorithm for grouping data points into clusters.

Machine Learning Fundamentals

Covers the fundamental concepts of machine learning, including classification, algorithms, optimization, supervised learning, reinforcement learning, and various tasks like image recognition and text generation.

Shape from Shading: Recovering 3D Information from 2D Images

Covers the techniques for recovering 3D shape information from 2D images using shading models and modern deep learning approaches.

K-means Clustering: Initialization and Image Segmentation

Explores k-means clustering, emphasizing initialization and image segmentation.

Segmentation: Techniques and Applications

Explores segmentation techniques, including CNNs and U-Net models, for image recognition and analysis, emphasizing time-saving automated methods.

Deep Learning: Edge Detection and Neural Networks

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

All Projects: Overview

Covers various projects related to measuring, analyzing, and quantifying different biological processes.

Image Processing in Fiji

Covers the basics of image processing using Fiji software, focusing on managing files and applying filters.

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