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Image Processing I: Edge Detection and Texture Analysis
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Computer Vision Basics: Image Processing and Feature Detection
Covers the basics of computer vision, focusing on image processing techniques and feature detection.
Image Processing I: Correlation Measures and Matched Filtering
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Image Processing: Neighborhood Averaging & Gaussian Smoothing
Explores neighborhood averaging, Gaussian smoothing, median filtering, contrast enhancement, and edge detection in image processing.
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Discusses edge detection techniques and the evolution of deep learning in neural networks.
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Delves into the mathematical foundations and importance of directional cues in image processing, exploring computational challenges and selectivity to orientation.
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Introduces image processing basics in Python, covering manipulation, grayscale conversion, edge detection, and convolution with kernels.
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Explores the evolution of edge detection techniques, from Canny to deep learning insights.
Directional Image Analysis: Steerable Filters
Explores directional image analysis and the implementation of steerable filters for edge and ridge detection.
Topology: Polyhedral Products and Edge Detection
Explores topology concepts and edge detection in computer vision, highlighting the significance of contours and gradients in image analysis.
