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ORCIDChia-Yu Hsu 0001
Person information
- affiliation: Arizona State University, School of Geographical Sciences and Urban Planning, Spatial Analysis Research Center (SPARC), Tempe, AZ, USA
Other persons with the same name
- Chia-Yu Hsu — disambiguation page
- Chia-Yu Hsu 0002
![[0000-0003-3581-4090]](https://dblp.org/img/orcid-mark.12x12.png "0000-0003-3581-4090")
— Kyoto University, Graduate School of Informatics, Kyoto, Japan - Chia-Yu Hsu 0003 — Yuan Ze University, Department of Information Mangement, Chungli, Taiwan (and 1 more)
- Chia-Yu Hsu 0004 — National Taiwan University, Graduate Institute of Communication Engineering, Taipei, Taiwan (and 1 more)
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2020 – today
- 2025
[j8]Sizhe Wang, Wenwen Li, Chia-Yu Hsu:
STEPNet: A Spatial and Temporal Encoding Pipeline to Handle Temporal Heterogeneity in Climate Modeling Using AI: A Use Case of Sea Ice Forecasting. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 18: 4921-4935 (2025)- [i9]Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Zhining Gu, Yili Yang, Brendan M. Rogers, Anna Liljedahl:
A multi-scale vision transformer-based multimodal GeoAI model for mapping Arctic permafrost thaw. CoRR abs/2504.17822 (2025) - 2024
- [j7]Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Yezhou Yang, Hyunho Lee, Anna Liljedahl, Chandi Witharana, Yili Yang, Brendan M. Rogers, Samantha T. Arundel, Matthew B. Jones, Kenton McHenry, Patricia Solís:
Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model's Generalizability in Permafrost Mapping. Remote. Sens. 16(5): 797 (2024) - [i8]Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Yezhou Yang, Hyunho Lee, Anna Liljedahl, Chandi Witharana, Yili Yang, Brendan M. Rogers, Samantha T. Arundel, Matthew B. Jones, Kenton McHenry, Patricia Solís:
Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model's Generalizability in Permafrost Mapping. CoRR abs/2401.08787 (2024) - [i7]Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Peter Kedron:
GeoAI Reproducibility and Replicability: a computational and spatial perspective. CoRR abs/2404.10108 (2024) - [i6]Chia-Yu Hsu, Wenwen Li, Sizhe Wang:
Geospatial foundation models for image analysis: evaluating and enhancing NASA-IBM Prithvi's domain adaptability. CoRR abs/2409.00489 (2024) - [i5]Daniela Szwarcman, Sujit Roy, Paolo Fraccaro, Þorsteinn Elí Gíslason, Benedikt Blumenstiel, Rinki Ghosal, Pedro Henrique de Oliveira, João Lucas de Sousa Almeida, Rocco Sedona, Yanghui Kang, Srija Chakraborty, Sizhe Wang, Ankur Kumar, Myscon Truong, Denys Godwin, Hyunho Lee, Chia-Yu Hsu, Ata Akbari Asanjan, Besart Mujeci, Trevor Keenan, Paulo Arevalo, Wenwen Li, Hamed Alemohammad, Pontus Olofsson, Christopher Hain, Robert Kennedy, Bianca Zadrozny, Gabriele Cavallaro, Campbell D. Watson, Manil Maskey, Rahul Ramachandran, Juan Bernabé-Moreno:
Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications. CoRR abs/2412.02732 (2024) - 2023
- [j6]Wenwen Li, Sizhe Wang, Samantha T. Arundel, Chia-Yu Hsu:
GeoImageNet: a multi-source natural feature benchmark dataset for GeoAI and supervised machine learning. GeoInformatica 27(3): 619-640 (2023) - [j5]Wenwen Li, Sizhe Wang, Samantha T. Arundel, Chia-Yu Hsu:
Correction to: GeoImageNet: a multi-source natural feature benchmark dataset for GeoAI and supervised machine learning. GeoInformatica 27(3): 643 (2023) - [j4]Chia-Yu Hsu, Wenwen Li:
Explainable GeoAI: can saliency maps help interpret artificial intelligence's learning process? An empirical study on natural feature detection. Int. J. Geogr. Inf. Sci. 37(5): 963-987 (2023) - [c4]Wenwen Li, Hyunho Lee, Sizhe Wang, Chia-Yu Hsu, Samantha T. Arundel:
Assessment of a new GeoAI foundation model for flood inundation mapping. GeoAI@SIGSPATIAL 2023: 102-109 - [i4]Chia-Yu Hsu, Wenwen Li:
Explainable GeoAI: Can saliency maps help interpret artificial intelligence's learning process? An empirical study on natural feature detection. CoRR abs/2303.09660 (2023) - [i3]Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Chandi Witharana, Anna Liljedahl:
Real-time GeoAI for High-resolution Mapping and Segmentation of Arctic Permafrost Features. CoRR abs/2306.05341 (2023) - [i2]Wenwen Li, Hyunho Lee, Sizhe Wang, Chia-Yu Hsu, Samantha T. Arundel:
Assessment of IBM and NASA's geospatial foundation model in flood inundation mapping. CoRR abs/2309.14500 (2023) - 2022
- [j3]Wenwen Li, Chia-Yu Hsu:
GeoAI for Large-Scale Image Analysis and Machine Vision: Recent Progress of Artificial Intelligence in Geography. ISPRS Int. J. Geo Inf. 11(7): 385 (2022) - [c3]Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Chandi Witharana, Anna Liljedahl:
Real-time GeoAI for high-resolution mapping and segmentation of arctic permafrost features: the case of ice-wedge polygons. GeoAI@SIGSPATIAL 2022: 62-65 - 2021
- [j2]Chia-Yu Hsu, Wenwen Li, Sizhe Wang:
Knowledge-Driven GeoAI: Integrating Spatial Knowledge into Multi-Scale Deep Learning for Mars Crater Detection. Remote. Sens. 13(11): 2116 (2021) - [i1]Chia-Yu Hsu, Wenwen Li:
Learning from Counting: Leveraging Temporal Classification for Weakly Supervised Object Localization and Detection. CoRR abs/2103.04009 (2021) - 2020
- [j1]Wenwen Li, Chia-Yu Hsu:
Automated terrain feature identification from remote sensing imagery: a deep learning approach. Int. J. Geogr. Inf. Sci. 34(4): 637-660 (2020) - [c2]Chia-Yu Hsu, Wenwen Li:
Learning from Counting: Leveraging Temporal Classification for Weakly Supervised Object Localization and Detection. BMVC 2020
2010 – 2019
- 2017
- [c1]Wenwen Li, Bin Zhou, Chia-Yu Hsu, Yixing Li, Fengbo Ren:
Recognizing terrain features on terrestrial surface using a deep learning model: an example with crater detection. GeoAI@SIGSPATIAL 2017: 33-36
Coauthor Index
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