Lectures related to Concept-Based Image Systems

Texture Analysis: Statistical and Structural Approaches

Discusses texture analysis in images, focusing on statistical and structural properties, segmentation techniques, and machine learning applications for texture classification.

Drone Imaging Analysis

Explores drone imaging analysis using Meshroom software for civil engineering applications.

Dose Management in Electron Microscopy

Explores the challenges and solutions for managing electron dose in microscopy, emphasizing the importance of accurate dose tracking and analysis.

Shape from Shading and Texture

Covers shape from shading, texture, reflectance maps, and specularities in computer vision.

Computer Vision: Fundamentals and Applications

Covers the fundamentals of computer vision, illusions, challenges, applications, and history.

Texture: Analysis and Classification

Explores the analysis and classification of texture in images, emphasizing the role of Machine Learning techniques like Convolutional Neural Networks.

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.

Computer Vision: Image Formation and Transformation

Provides an overview of image formation and transformation principles in computer vision.

Image Classification: Decision Trees & Random Forests

Explores image classification using decision trees and random forests to reduce variance and improve model robustness.

X-ray Tomography Practical Analysis

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

Procedural Content Generation

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.