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Automatic Vectorization: Principles and Applications

Covers the potential and limits of automatic vectorization techniques for digitizing objects from scanned documents or images.

Ground Penetrating Radar: Data Analysis

Explores the automated picking of reinforcement bars within Ground Penetrating Radar data using machine learning and signal processing techniques.

Machine Learning Fundamentals

Covers fundamental principles, opportunities, and challenges in machine learning.

Detecting Objects: Independent Channels

Emphasizes the need for independent channels when detecting objects in images.

Transformers in Visual Intelligence

Explores transformers in visual intelligence, focusing on object detection, image synthesis, and feature fusion.

Proper Feature Size: Image Analysis

Delves into choosing a proper feature size for image analysis in life sciences, presenting a Rule Of Thumb for defining object size in pixels.

Probability Distributions in Environmental Studies

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.

Image Processing I: Discrete Histogram Processing and Spatial Operators

Explores discrete histogram processing and spatial operators for image manipulation and noise reduction.

Uncertainty Quantification and Label Error Detection

Explores uncertainty quantification and label error detection in deep learning for semantic segmentation, focusing on challenges and methods for error detection.

Edge Detection: Basics and Techniques

Introduces the basics of edge detection, including measuring contrast, gradient images, Fourier interpretation, Gaussian functions, Canny edge detector, and industrial applications.