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Related lectures (10)
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Image Filtering: Basics and Techniques
Explores image filtering techniques, including linear and nonlinear filters, for artifact removal and feature enhancement.
Image Processing: Smoothing and Filtering
Covers image smoothing, noise reduction, and segmentation techniques using filters and transforms.
Image Processing: Neighborhood Averaging & Gaussian Smoothing
Explores neighborhood averaging, Gaussian smoothing, median filtering, contrast enhancement, and edge detection in image processing.
Cloud computing support for IoT
Explores the evolution of cloud computing to support IoT applications and the challenges faced by deep learning algorithms in processing data from smart sensors.
Image Filtering: Classic Filters
Explores classic image filters like Moving Average, Gaussian Blur, Sobel filter, and Laplacian operator.
Signal Processing: Noise Filtering and Signal Estimation
Explores noise filtering, signal estimation, and signal-to-noise ratio optimization through Wiener-Khintchine theorem and power spectral density.
Image Processing I
Introduces the basics of image processing, covering point and spatial operators, histogram processing, and transform-domain operations.
Image Processing Techniques
Covers image processing techniques including noise addition, filtering, and image enhancement using various filters and tools.
Image Processing: Enhancement and Analysis
Explores image processing techniques such as contrast manipulation, enhancement, and sharpening using Fiji software.
Taxonomy Induction: Relations Extraction and Graph Construction
Covers relations extraction and graph construction in taxonomy induction, emphasizing noise reduction for accurate graphs.
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