Explore reinforced active learning for image segmentation in this 24-minute video from Launchpad. Delve into the challenges and examples of image segmentation, and learn about reinforcement learning techniques for optimal policy development. Examine the main paper's findings, including compact and action representations. Discover the architecture of reinforced active learning and analyze experimental results with varying numbers of regions. Gain insights into this innovative approach to image segmentation through detailed explanations of algorithms, experimental settings, and comparisons with baselines.
Overview
Syllabus
Introduction
Challenges
Example
Reinforcement Learning
Optimal Policy
Algorithms
Main paper
Representation
Compact representations
Action representation
Reinforced active learning
Architecture
Experiments
Experimental settings
Baselines
Experimental results
Experiments with varying number of regions
Conclusion
Taught by
Launchpad
