Deep Reinforcement Learning-Based DQN Agent Algorithm for Visual Object Tracking in a Virtual Environmental Simulation

Deep Reinforcement Learning-Based DQN Agent Algorithm for Visual Object Tracking in a Virtual Environmental Simulation

The complexity of object tracking models among hardware applications has become a more in-demand task to accomplish with multifunctional algorithm skills in various indeterminable environment tracking conditions. Experimenting with the virtual realistic simulator brings new dependencies and requirem...

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Bibliographic Details
Main Authors: Jin-Hyeok Park, Khurshedjon Farkhodov, Suk-Hwan Lee, Ki-Ryong Kwon
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Applied Sciences
Subjects:
object tracking
object detection
deep learning
deep reinforcement learning
deep Q-network
DQN
Online Access:https://www.mdpi.com/2076-3417/12/7/3220

Internet

https://www.mdpi.com/2076-3417/12/7/3220

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