Delineation: Techniques and Applications

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Related lectures (28)

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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.

Deep Learning: Edge Detection and Neural Networks

Discusses edge detection techniques and the evolution of deep learning in neural networks.

Edge Detection: Deep Learning Insights

Explores the evolution of edge detection techniques, from Canny to deep learning insights.

Machine Learning Fundamentals

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

Social Media Images: Understanding Food Perception with Deep Learning

Explores deep learning with Instagram images, understanding food perception, obesity, and mental health, and discusses the impact of social media images and ephemeral platforms like Snapchat.

Visual Intelligence: Projects and Challenges

Explores projects and challenges in visual intelligence, including hands-on learning and analysis of vision methods.

Social Image Systems: From Past to Present

Explores the evolution of social image systems, deep learning models, selfies, and biometrics in online platforms.

Convolutional Neural Networks

Introduces Convolutional Neural Networks (CNNs) for autonomous vehicles, covering architecture, applications, and regularization techniques.

Computer Vision: Historical Insights and Project Inspirations

Explores the historical development of computer vision and inspires innovative project ideas.

Perception: Data-Driven Approaches

Explores perception in deep learning for autonomous vehicles, covering image classification, optimization methods, and the role of representation in machine learning.