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A Multi-Level Corroborative Approach for Verification and Validation of Autonomous Robotic Swarms
We explore our approach through a case study focused on a swarm of robots operating within a public cloakroom.
A Multigraph Representation for Improved Unsupervised/Semi-supervised Learning of Human Actions
Graph-based methods are a useful class of methods for improving the performance of unsupervised and semi-supervised machine learning tasks, such as clustering or information retrieval.
Unsupervised Spectral Dual Assignment Clustering of Human Actions in Context
A recent trend of research has shown how contextual information related to an action, such as a scene or object, can enhance the accuracy of human action recognition systems.
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