@inproceedings{e5e7a8f1c0684b1d834fc3b48ac22c07,
title = "The new SSD image detection for quadcopter platform control simulation",
abstract = "Image processing and machine learning has fast progress in this era. Machine learning also has been applicate in our daily life. One of machine learning application is an object detection. This paper shows a state-of-the-art of object detection is applicated on control system. This paper also gives a deliberation by comparing another trained state-of-the- A rt (YOLOv3-tiny-416 and SSD with MobileNet V2) to detect single object i.e. person. SSD is one state-of-the-art of object detection which concept is to detect object in a single forward (one-shot) to feature extraction and classifier. Our work develops the feature extractor layer of SSD to fit with our purpose and show our modified SSD successfully control quadcopter movements feedback and has an average precision (AP) 97% to detect person. Quadcopter controls is completed by a simulation in gazebo simulator. ",
author = "Alfarih Faza and Darma, {Surya Surya} and Santoso Sukirno",
note = "Funding Information: This work was supported by Hibah PITTA (Publikasi Internasional Terindeks untuk Tugas Akhir Mahasiswa Universitas Indonesia) B 2019 funded by DRPM Universitas Indonesia. Grant contract number NKB0663/UN2.R3.1/HKP.05.00/2019. Publisher Copyright: {\textcopyright} 2020 Author(s).; 2nd International Conference on Physical Instrumentation and Advanced Materials, ICPIAM 2019 ; Conference date: 22-10-2019",
year = "2020",
month = dec,
day = "9",
doi = "10.1063/5.0035018",
language = "English",
series = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",
editor = "Herri Trilaksana and Harun, {Sulaiman Wadi} and Cameron Shearer and Moh Yasin",
booktitle = "2nd International Conference on Physical Instrumentation and Advanced Materials 2019",
address = "United States",
}