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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Uncertainty-Aware Quality Control of Airborne Bathymetric LiDAR Point Clouds in Tidal Flats: A Data-Driven Approach
Song, A., 2026, In: IEEE Geoscience and Remote Sensing Letters. 23, 6500405.Research output: Contribution to journal › Article › peer-review
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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 Access4 Scopus citations -
Assessment of the Segment Anything Model’s Applicability to Coastal Debris Segmentation: A Comparative Analysis of Prompt input Methods
Song, A., Jun 2025, In: Korean Journal of Remote Sensing. 41, 3, p. 593-603 11 p.Research output: Contribution to journal › Article › peer-review
Open Access -
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 Access2 Scopus citations -
Improving Object-Oriented Small Chimney Detection Performance in High-Resolution Satellite Imagery via Targeted Augmentation Strategies
Amadin, V., Lee, J., Lee, K., Kim, Y., Song, A. & Han, Y., Dec 2025, In: Korean Journal of Remote Sensing. 41, 6, p. 1131-1149 19 p.Research output: Contribution to journal › Article › peer-review
Open Access