Image segmentation

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Related lectures (30)

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Image Processing I

Covers fundamental concepts in image processing, including preprocessing techniques and matching methods.

Convolutional Neural Networks: Semantic Segmentation

Explores Convolutional Neural Networks for semantic segmentation, discussing models for pixel classification, learned decoding, and the importance of skip connections.

Image Processing I: Segmentation and Thresholding

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

Image Processing Fundamentals

Covers the basics of image processing for microscopy, including acquiring, correcting defects, enhancing images, and extracting information.

Image Processing in Frequency Space

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

Image Processing: Smoothing and Filtering

Covers image smoothing, noise reduction, and segmentation techniques using filters and transforms.

Image Processing: Enhancement and Analysis

Explores image processing techniques such as contrast manipulation, enhancement, and sharpening using Fiji software.

Image Processing Techniques

Covers image processing techniques including noise addition, filtering, and image enhancement using various filters and tools.

X-ray Tomography Practical Analysis

Covers the practical analysis of X-ray tomography images using Fiji software.

Deep Learning: Edge Detection and Neural Networks

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