Classification Of Forest And Land Fires Using The You Only Learn One Representation algorithm
Keywords:
Forest fires, digital imagery, You Only Learn One Representation (YOLOR)
Abstract
Forest areas have a function of storing carbon dioxide and producing oxygen from trees and plants. The function of forests is very important for life, so forests are highly protected. One solution that can be taken is to take preventive measures, namely monitoring fire hotspots in forest and land areas by air. This research was tested using the same dataset as the YOLO (You Only Look Once) algorithm against the You Only Learn One Representation (YOLOR) algorithm with a train data division model of 1188 image data and test data of 75 image data with mAP results of 66.36%. . So it can be confirmed that the YOLOR algorithm is better than the YOLO algorithm which gets an mAP value of 50.65%.
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References
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Wang, C.-Y., Yeh, I.-H. and Liao, H.-Y. M. (2021) ‘You Only Learn One Representation: Unified Network for Multiple Tasks’, pp. 1–11. Available at: http://arxiv.org/abs/2105.04206.
Sanjaya, J. and Ayub, M. (2020) ‘Augmentasi Data Pengenalan Citra Mobil Menggunakan Pendekatan Random Crop, Rotate, dan Mixup’, Jurnal Teknik Informatika dan Sistem Informasi, 6(2), pp. 311–323. doi: 10.28932/jutisi.v6i2.2688.
Gunadi, K., Setyati, E. and Surabaya, J. S. (2020) ‘Deteksi Helm pada Pengguna Sepeda Motor dengan Metode Convolutional Neural Network’, Jurnal Infra, 8(1), pp. 295–301.
Al amin, I. H. and Aprilino, A. (2022) ‘Implementasi Algoritma Yolo Dan Tesseract Ocr Pada Sistem Deteksi Plat Nomor Otomatis’, Jurnal Teknoinfo, 16(1), p. 54. doi: 10.33365/jti.v16i1.1522.
Benjdira, B. et al. (2018) ‘Car Detection using Unmanned Aerial Vehicles: Comparison between Faster R-CNN and YOLOv3’.
Bochkovskiy, A., Wang, C. Y. and Liao, H. Y. M. (2020) ‘YOLOv4: Optimal Speed and Accuracy of Object Detection’, arXiv.
Expert System Team (2020) What is Machine Learning? A Definition.
Fikriya, Z. A., Irawan, M. I. and Soetrisno., S. (2017) ‘Implementasi Extreme Learning Machine untuk Pengenalan Objek Citra Digital’, Jurnal Sains dan Seni ITS, 6(1). doi: 10.12962/j23373520.v6i1.21754.
Goyal, S. et al. (2020) ‘A YOLO based Technique for Early Forest Fire Detection’, International Journal of Innovative Technology and Exploring Engineering, 9(4), pp. 1357–1362. doi: 10.35940/ijitee.f4106.049620.
Hu, J. et al. (2019) ‘Detection of Workers Without the Helments in Videos Based on YOLO V3’, International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) Detection.
Kemal Putra, I., Hero Saharjo, B. and Wasis, B. (2019) ‘Institutional Challenge on Forest and Land Fire Management at the Site Level’, Jurnal Ilmu Pertanian Indonesia, 24(2), pp. 151–159. doi: 10.18343/jipi.24.2.151.
Li, G. et al. (2020) ‘Small Boat Detection for Radar Image Datasets with YOLO V3 Network’, (d), pp. 46–50.
Nurdin, A. S. (2018) ‘Pengaruh Iklim Global Terhadap Kebakaran Hutan Di Kota Ternate’, Techno: Jurnal Penelitian, 7(2), p. 150. doi: 10.33387/tk.v7i2.713.
Published
2023-12-31
How to Cite
Rizki, Y., Yogi Alfinaldo, Soni, Sy, Y. S., & Rahmad Firdaus. (2023). Classification Of Forest And Land Fires Using The You Only Learn One Representation algorithm. Jurnal CoSciTech (Computer Science and Information Technology), 4(3), 832-837. https://doi.org/10.37859/coscitech.v4i3.6434
Section
Articles
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