@inproceedings{91415beccf8141cb86800329846d0fac,
title = "Low Latency and Non-Intrusive Accurate Object Detection in Forests",
keywords = "4G/5G, Low-latency, Tree species detection, WebRTC, YOLOv5",
author = "Ambreen Hussain and Bidushi Barua and Ahmed Osman and Raouf Abozariba and Asyhari, {A. Taufiq}",
note = "Funding Information: This work was funded by the Department for Digital, Culture, Media & Sport (DCMS) as part of the 5G Connected Forest (5GCF) project under its 5G Testbeds and Trials Program. ∗The corresponding authors for this work are Ambreen Hussain and A. Taufiq Asyhari. Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 ; Conference date: 05-12-2021 Through 07-12-2021",
year = "2021",
doi = "10.1109/SSCI50451.2021.9660175",
language = "English",
series = "2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings",
}