Concept-Based Image Systems

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Related lectures (29)

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Explores procedural content generation using noise functions to create realistic terrains and textures with control over roughness.

Delineation: Techniques and Applications

Explores techniques for delineation, including Hough transform, gradient orientation, and shape detection, emphasizing the importance of combining graph-based techniques and machine learning.

Document Segmentation: dhSegment

Explores the development and improvements of dhSegment, an open-source document segmentation package using PyTorch.

Image Processing: Enhancement and Analysis

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

Image Processing I

Covers the basics of image processing and its applications in various fields.

Procedural Techniques: L-Systems

Covers procedural techniques in computer graphics, focusing on L-Systems for plant modeling and intricate graphical patterns.

Visual Intelligence: Projects and Challenges

Explores projects and challenges in visual intelligence, including hands-on learning and analysis of vision methods.

Quantitative Imaging for Civil Engineers

Introduces quantitative imaging concepts for civil engineers, covering resolution, optics, image quality, and 3D measurements.

Computer Vision Basics: Image Processing and Feature Detection

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

Deep Learning: Convolutional Neural Networks

Covers Convolutional Neural Networks, standard architectures, training techniques, and adversarial examples in deep learning.