Deep Reinforcement Learning Tf-Agent-Based Object Tracking With Virtual Autonomous Drone in a Game Engine-Reference-Cited by-同舟云学术

Deep Reinforcement Learning Tf-Agent-Based Object Tracking With Virtual Autonomous Drone in a Game Engine

Published:2023 Issue: Volume:11 Page:124129-124138
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Farkhodov Khurshedjon¹^ORCID,Lee Suk-Hwan²,Platos Jan³^ORCID,Kwon Ki-Ryong¹^ORCID

Affiliation:

1. Department of AI Convergence, Pukyong National University, Busan, South Korea

2. Department of Computer Engineering, Dong-A University, Busan, South Korea

3. Department of Electrical Engineering and Computer Science, VSB—Technical University of Ostrava, Ostrava, Czech Republic

Funder

Ministry of Science and Information and Communication Technology (MSIT), South Korea, through the Information Technology Research Center (ITRC) Support Program

Institute for Information and Communications Technology Planning and Evaluation

MSIT through the ICT Consilience Creative Program, Supervised by the IITP

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10286478.pdf?arnumber=10286478

Reference39 articles.

1. Visual Object Tracking in Drone Images with Deep Reinforcement Learning

2. Reinforcement Cutting-Agent Learning for Video Object Segmentation

3. LSTM network with tracking association for multi-object tracking;farhodov;Korea Multimedia Society Journal,2020

4. Multi-Agent Reinforcement Learning Based Frame Sampling for Effective Untrimmed Video Recognition

5. Unity: A general platform for intelligent agents;juliani;arXiv 1809 02627,2018

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