Research output per year
Research output per year
Personal profile
In Korean
송아람 교수(과학기술대학 위치정보시스템학과)
Education
(2012) B.A., Inha University, Inchen
(2019) Ph.D., Seoul National University, Seoul
(2019) Ph.D., Seoul National University, Seoul
Professional Experience
o (2021.09~) Assistant Professor, Kyungpook National University, Sangju, Korea
o (2020.09~2021.01) Postdoctoral researcher, BK21 four InfraSphere education Research Group, Seoul National University, Seoul, Korea
o (2020.09-2020.12) Lecturer, Chungbuk National University, Cheongju, Korea
o (2020.09-2020.12) Lecturer, Kyungpook National University, Sangju, Korea
o (2019.09~2020.08) Postdoctoral researcher, BK21 plus next-generation construction value creation Leader Training Division, Seoul National University, Seoul, Korea
o (2017.11~2019.08) Researcher, Institute of Engineering Research, Seoul National University, Seoul, Korea
o (2020.09~2021.01) Postdoctoral researcher, BK21 four InfraSphere education Research Group, Seoul National University, Seoul, Korea
o (2020.09-2020.12) Lecturer, Chungbuk National University, Cheongju, Korea
o (2020.09-2020.12) Lecturer, Kyungpook National University, Sangju, Korea
o (2019.09~2020.08) Postdoctoral researcher, BK21 plus next-generation construction value creation Leader Training Division, Seoul National University, Seoul, Korea
o (2017.11~2019.08) Researcher, Institute of Engineering Research, Seoul National University, Seoul, Korea
Research Interests
Remote Sensing
Change Detection
Deep Learning
Change Detection
Deep Learning
Major Research Achievements
o Hybrid approach using deep learning and graph comparison for building change detection
o Change detection in hyperspectral images using recurrent 3D fully convolutional networks
o Uncertainty analysis for object-based change detection in very high-resolution satellite images using deep learning network
o Fully convolutional networks with multiscale 3D filters and transfer learning for change detection in high spatial resolution satellite images
o Change detection in hyperspectral images using recurrent 3D fully convolutional networks
o Uncertainty analysis for object-based change detection in very high-resolution satellite images using deep learning network
o Fully convolutional networks with multiscale 3D filters and transfer learning for change detection in high spatial resolution satellite images
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Advanced Building Detection with Faster R-CNN Using Elliptical Bounding Boxes for Displacement Handling
Jung, S., Song, A., Lee, K. & Lee, W. H., Apr 2025, In: Remote Sensing. 17, 7, 1247.Research output: Contribution to journal › Article › peer-review
Open Access2 Scopus citations -
Deep learning applications on satellite imagery datasets for nuclear nonproliferation and counter-proliferation
Han, J. J., Ha, G., Han, Y., Lee, C., Lee, H. & Song, A., 1 Sep 2025, In: Annals of Nuclear Energy. 219, 111443.Research output: Contribution to journal › Article › peer-review
Open Access -
SD2GC-F: Enhancing Building Change Detection With Sequential Detection to Graph Comparison Framework
Song, A. & Park, S., 2025, In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18, p. 21840-21854 15 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Deep Learning Approach for Classification of Water Bottom and Surface from Bathymetric Lidar Point Clouds
Song, A. & Kim, H., 2024, IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Proceedings. Institute of Electrical and Electronics Engineers Inc., p. 6069-6071 3 p. (International Geoscience and Remote Sensing Symposium (IGARSS)).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Seabed Segmentation of Airborne Bathymetric Light Detection and Ranging Point Cloud Using Window-based Attention and Orthogonal Regularized PointNet
Song, A. & Lee, J., 2024, In: Sensors and Materials. 36, 9, p. 3997-4015 19 p.Research output: Contribution to journal › Article › peer-review
Open Access