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Cognitive Radio Resource Scheduling using Multi agent QLearning for LTE
The first type of the scheduled users is the Primary Users, and they are the licensed subscribers that pay for their service.
A deep Q-Learning based Path Planning and Navigation System for Firefighting Environments
Live fire creates a dynamic, rapidly changing environment that presents a worthy challenge for deep learning and artificial intelligence methodologies to assist firefighters with scene comprehension in maintaining their situational awareness, tracking and relay of important features necessary for key decisions as they tackle these catastrophic events.
A Novel Indoor Positioning System for unprepared firefighting scenarios
Situational awareness and Indoor location tracking for firefighters is one of the tasks with paramount importance in search and rescue operations.
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