과제정보
This work was supported by Seokyeong University in 2021
참고문헌
- Jong-Chan Park, Dae-Seong Kang, "Real-time video fire detection based on YOLO in antifire aurveillance systems," Proceedings of KIIT conference, KIIT, pp.179-181, 2021. DOI: 10.1007/s11554-020-01044-0
- Geun-Su Kim, Gyu-Do Park, and Soo-Hyeok Kang, "Fire Identification Embedded System Using YOLO algorithm," Proceedings of IEEK conference, pp.1920-1923, 2021.
- Young-Jin Kim, Eun-Gyung Kim, "Image based Fire Detection using Convolutional Neural Network," Journal of the Korea Institute of Information and Communication Engineering, Vol.20, No.9, pp. 1649-1656, 2016. DOI: 10.6109/jkiice.2016.20.9.1649
- J. Redmon, et. al., "You Only Look Once: Unified, Real-Time Object Detection," in Proc. CVPR, 2016. DOI: 10.48550/arXiv.1506.02640
- W. Liu, et. al., "SSD: Single Shot MultiBox Detector," in Proc. ECCV, 2016.
- T.-Y. Lim, et. al., "Focal Loss for Dense Object Detection," in Proc. ICCV, 2017.
- R. Girshick, et. al., "Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmenation," in Proc. CVPR, 2014.
- R. Girshick, "Fast R-CNN," in Proc. ICCV, 2015. DOI: 10.1109/CVPR.2014.81
- S. Ren, "Faster R-CNN: Toward Real-Time Object Detection with Region Proposal Networks," in Proc. NeurIPS, 2015.
- Jun-Mock Lee, Dae-Sung Kang, "Optimizing data augmentation based few-shot learning method for improving indoor fire detection accuracy," in Proc. Korea Digital Contents Societry, pp.237-240, 2019.
- I. Goodfellow, J. Pouget-Abadie and M. Mirza, "Generative Adversarial Networks," Neural Information Processing Systems, Vol.2, pp.2672-2680, 2014. DOI: 10.1109/MSP.2017.2765202
- You-min Na, Dong-hwan Hyun, Do-hyun Park, Se-hyun Hwang, Soo-hong Lee, "AI Fire Detection & Notification System," Journal of the Korea Society of Computer and Information, Vol.25, No.12, pp63-71, 2020. DOI: 10.9708/jksci.2020.25.12.063
- Cubuk, E. D., Zoph, B., Mane, D., Vasudevan, V., & Le, Q. V., "Autoaugment: Learning augmentation policies from data," arXiv preprint arXiv:1805.09501., 2018.
- M. Tan, et. al., "EfficientDet: Scalable and Efficient Object Detection," in Proc. CVPR, 2020.
- Bochkovskiy, Alexey, Chien-Yao Wang, and Hong-Yuan Mark Liao, "YOLOv4: Optimal Speed and Accuracy of Object Detection," arXiv preprint arXiv:2004.10934, 2020.
- Jae-Jung Kim, Jin-Kyu Ryu, Dong-Kurl Kwak, Sun-Joon Byun, "A Study on Flame Detection using Faster R-CNN and Image Augmentation Techniques," j.inst.Korean.electr. electron.eng., Vol.22, No.4, pp.1079-1087, 2018. http://dx.doi.org/10.7471/ikeee. 2018.22.4. 1079.
- Jonathan Hui, "mAP (mean Average Precision) for Object Detection,"https://jonathan-hui.medium.com/map-mean-average-precision-for-objectdetection-45c121a31173