Aerial Insights: Deep Learning-Based Human Action Recognition in Drone Imagery-Reference-Cited by-同舟云学术

Aerial Insights: Deep Learning-Based Human Action Recognition in Drone Imagery

Published:2023 Issue: Volume:11 Page:83946-83961
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Azmat Usman¹,Alotaibi Saud S.²,Abdelhaq Maha³,Alsufyani Nawal⁴,Shorfuzzaman Mohammad⁴,Jalal Ahmad¹^ORCID,Park Jeongmin⁵^ORCID

Affiliation:

1. Department of Computer Science, Air University, Islamabad, Pakistan

2. Information Systems Department, Umm Al-Qura University, Macca, Saudi Arabia

3. Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

4. Department of Computer and Information, Prince Sultan University, Riyadh, Saudi Arabia

5. Department of Computer Engineering, Tech University of Korea, Siheung-si, Gyeonggi-do, South Korea

Funder

Basic Science Research Program through the National Research Foundation

Ministry of Science and Information & Communications Technology (MSIT), Republic of Korea

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/ielx7/6287639/10005208/10210047.pdf?arnumber=10210047

Reference66 articles.

1. UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicles

2. Automatic Recognition of Human Interaction via Hybrid Descriptors and Maximum Entropy Markov Model Using Depth Sensors

3. Drone-Action: An Outdoor Recorded Drone Video Dataset for Action Recognition

4. Ridge body parts features for human pose estimation and recognition from RGB-D video data

5. P-CNN: Pose-based CNN features for action recognition;chéron;Proc IEEE Int Conf Comput Vis (ICCV),2015

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