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Related lectures (30)
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.
Edge Detection: Deep Learning Insights
Explores the evolution of edge detection techniques, from Canny to deep learning insights.
Machine Learning FundamentalsMOOC: Humanitarian Action in the Digital Age
Covers fundamental principles, opportunities, and challenges in machine learning.
Computer Vision Basics: Image Processing and Feature Detection
Covers the basics of computer vision, focusing on image processing techniques and feature detection.
Social Image Systems: From Past to Present
Explores the evolution of social image systems, deep learning models, selfies, and biometrics in online platforms.
Directional Image Analysis and Processing
Delves into the mathematical foundations and importance of directional cues in image processing, exploring computational challenges and selectivity to orientation.
Evaluating Machine Accuracy and Robustness on ImageNet
Explores the evaluation of machine and human accuracy and robustness on ImageNet, highlighting progress, challenges, and the need for improvement.
Shape from Contours
Explores shape reconstruction from contours using edge-based stereo matching and visual hull techniques for accurate 3D reconstruction.
Visual Intelligence: Embodied AI
Explores computer vision in embodied AI, covering object navigation and video generation from single images, with a focus on robustness and precision.
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.