Using the Mask R-CNN model for segmentation of real estate objects in aerial photographs
- Authors: Vinokurov I.V.1
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Affiliations:
- Financial University under the Government of the Russian Federation
- Issue: Vol 16, No 1 (2025)
- Pages: 3-44
- Section: Articles
- URL: https://bakhtiniada.ru/2079-3316/article/view/299217
- DOI: https://doi.org/10.25209/2079-3316-2025-16-1-3-44
- ID: 299217
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Abstract
About the authors
Igor Victorovich Vinokurov
Financial University under the Government of the Russian Federation
Email: igvvinokurov@fa.ru
Candidate of Technical Sciences (PhD), Associate Professor at the Financial University under the Government of the Russian Federation. Research interests: information systems, information technologies, data processing technologies
References
- T.-Y. Lin, P. Goyal, R. B. Girshick, K. He, P. Dollár. Focal loss for dense object detection, Computing Research Repository (CoRR), 2017, 10 pp.
- X. Wang, T. Kong, Ch. Shen, Y. Jiang, L. Li. SOLO: Segmenting objects by locations, Computing Research Repository (CoRR), 2019, 19 pp.
- K. Duda, A. Ivanov. „On decidability of amenability in computable groups“, Archive for Mathematical Logic, 61 (2022), pp. 891–902.
- K. He, G. Gkioxari, P. Dollár, R. B. Girshick. Mask R-CNN, Computing Research Repository (CoRR), 2017, 12 pp.
- S. Ren, K. He, R. B. Girshick, J. Sun. Faster R-CNN: Towards real-time object detection with region proposal networks, Computing Research Repository (CoRR), 2015, 14 pp.
- K. He, X. Zhang, S. Ren, J. Sun. Identity mappings in deep residual networks, Computing Research Repository (CoRR), 2016, 15 pp.
- T.-Y. Lin, M. Maire, S. J. Belongie, L. D. Bourdev, R. B. Girshick, J. Hays, P. Perona, D. Ramanan, P. Dollár, C. L. Zitnick. Microsoft COCO: Common objects in context, Computing Research Repository (CoRR), 2014, 15 pp.
- Y. Xu, L. Wu, Z. Xie, Z. Chen. „Building extraction in very high resolution remote sensing imagery using deep learning and guided filters“, Remote. Sens., 10:1 (2018), 144, 18 pp.
- Q. Han, Q. Yin, X. Zheng, Z. Chen. „Remote sensing image building detection method based on Mask R-CNN“, Complex Intell. Syst., 8 (2022), pp. 1847—1855.
- K. Zhao, J. Kang, J. Jung, G. Sohn. „Building extraction from satellite images using Mask R-CNN with building boundary regularization“, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (18–22 June 2018, Salt Lake City, UT, USA), IEEE, 4 pp.
- X. Nie, M. Duan, H. Ding, B. Hu, E. K. Wong. „Attention Mask R-CNN for ship detection and segmentation from remote sensing images“, IEEE Access, 8 (2020), pp. 9325–9334.
- M. Jenila Vincent, P. Varalakshmi. „Extraction of building footprint using MASK-RCNN for high resolution aerial imagery“, Environmental Research Communications, 6:7 (2024), 075015, 17 pp.
- X. Zhu, L. Hu, J. Wang. „Urban modern architecture recognition based on Mask-RCNN and ECA attention mechanism“, Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023) (13–15 October 2023, Lianyungang, China), Proc. SPIE, vol. 12980, 2024, ISBN 9781510672789.
- R. Raghavan, D. Chander Verma, D. Pandey, R. Anand, B. Kumar Pandey, H. Singh. „Optimized building extraction from high-resolution satellite imagery using deep learning“, Multimedia Tools and Applications, 81:29 (2022), pp. 42309–42323.
- D. Ulanov, A. Syrov. „Building footprint extraction based on RGBD satellite imagery“, CS230 Deep Learning (Winter 2020, Stanford University, CA), 2020, 11 pp.
- A. Solanki, R. K. Singh, B. Demeneze. „Aerial pictures semantic segmentation applying deep learning“, International Journal of Trendy Research in Engineering and Technology, 5:1 (2021), pp. 42–48.
- A. NourEldeen, M. E. Wahed. „Enhanced building footprint extraction from satellite imagery using Mask R-CNN and PointRend“, Bulletin of Electrical Engineering and Informatics, 5:13 (2024), pp. 3601–3608.
- K. He, X. Zhang, S. Ren, J. Sun. Deep residual learning for image recognition, Computing Research Repository (CoRR), 2015, 12 pp.
- Ch. J. Mills. PyTorch Mask R-CNN tutorial, GitHub repository, 2023 URL https://github.com/cj-mills/pytorch-mask-rcnn-tutorial-code.
- J. Redmon, S. Divvala, R. B. Girshick, A. Farhadi. You Only Look Once: Unified, real-time object detection, Computing Research Repository (CoRR), 2015, 10 pp.
- R. Khanam, M. Hussain. YOLOv11: An overview of the key architectural enhancements, 2024, 9 pp.
- T.-Y. Lin, P. Dollár, R. B. Girshick, K. He, B. Hariharan, S. J. Belongie. Feature pyramid networks for object detection, Computing Research Repository (CoRR), 2016, 10 pp.
- A. Waleed. Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow, GitHub repository, 2017 URL https://github.com/matterport/Mask_RCNN.
- E. Stevens, L. Antiga, T. Viehmann. Deep Learning with PyTorch, Manning Publications, New York, 2020, ISBN 9781617295263, 520 pp.
- R. Sapkota, A. Dawood, M. Karkee. „Comparing YOLOv8 and Mask R-CNN for instance segmentation in complex orchard environments“, Artificial Intelligence in Agriculture, 13:1 (2024), pp. 84–99.
- V. F. Bulavitsky. „Use of drones to obtain aerial photographas terrain“, Elektronnoe nauchnoe izdanie «Uchyonye zametki TOGU», 4:4 (2013), pp. 1747–1755 (in Russian).
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