2021
AAAI
AAAI 2021
The Active Sensing Testbed
Abstract
Abstract The Active Sensing Testbed (AST) is a novel framework for research in machine perception and world-view rea-soning. The AST supports exploratory development of perception systems that can build internal models of the world by combining multi-view and multi-modal analyt-ics, utilize these models to form hypotheses about a sce-ne, and potentially take action to fill in gaps in knowledge or make predictions about future world states. As a modular software framework, the AST is in-tended to lower the barrier to entry for researchers and developers in applying state-of-the-art computer vision techniques to real-world problems.
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Interdisciplinary Bridge
— Artificial Intelligence and Computer Vision and Interdisciplinary and Machine Learning
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Keyword Pioneer
— world-view reasoning
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Hot Topic Early Bird
— world model
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Learning Types > Active Learning
Computer Vision > Analysis > Scene Understanding
Interdisciplinary > Cognitive Science > Perception
Artificial Intelligence > Core AI > Reasoning
Artificial Intelligence > Core AI > Computer Vision
Machine Learning > Learning Paradigms > Active Learning
Artificial Intelligence > Learning Paradigms > Active Learning