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1
Introduction
2
Challenges
3
Example
4
Reinforcement Learning
5
Optimal Policy
6
Algorithms
7
Main paper
8
Representation
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Compact representations
10
Action representation
11
Reinforced active learning
12
Architecture
13
Experiments
14
Experimental settings
15
Baselines
16
Experimental results
17
Experiments with varying number of regions
18
Conclusion
Description:
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.

Reinforced Active Learning for Image Segmentation

Launchpad
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