Chia-Yu Hsu

27 papers A 1Journal 23Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
A Multiscale Vision Transformer-Based Multimodal GeoAI Model for Mapping Arctic Permafrost Thaw.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens.
Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Zhining Gu, Yili Yang, Brendan M. Rogers, Anna Liljedahl
2025 J jnl
A multi-scale vision transformer-based multimodal GeoAI model for mapping Arctic permafrost thaw.
CoRR
Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Zhining Gu, Yili Yang, Brendan M. Rogers, Anna Liljedahl
2025 J jnl
Geospatial foundation models for image analysis: evaluating and enhancing NASA-IBM Prithvi's domain adaptability.
Int. J. Geogr. Inf. Sci.
Chia-Yu Hsu, Wenwen Li, Sizhe Wang
2025 J jnl
Landslide Hazard Mapping with Geospatial Foundation Models: Geographical Generalizability, Data Scarcity, and Band Adaptability.
CoRR
Wenwen Li, Sizhe Wang, Hyunho Lee, Chenyan Lu, Sujit Roy, Rahul Ramachandran, Chia-Yu Hsu
2025 J jnl
Pan-Arctic Permafrost Landform and Human-built Infrastructure Feature Detection with Vision Transformers and Location Embeddings.
CoRR
Amal Shehan Perera, David Fernandez, Chandi Witharana, Elias Manos, Michael Pimenta, Anna K. Liljedahl, Ingmar Nitze, Yili Yang, Todd Nicholson, Chia-Yu Hsu, Wenwen Li, Guido Grosse
2025 J jnl
RareFlow: Physics-Aware Flow-Matching for Cross-Sensor Super-Resolution of Rare-Earth Features.
CoRR
Forouzan Fallah, Wenwen Li, Chia-Yu Hsu, Hyunho Lee, Yezhou Yang
2025 J jnl
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.
Sizhe Wang, Wenwen Li, Chia-Yu Hsu
2024 J jnl
Advancing Arctic Sea Ice Remote Sensing with AI and Deep Learning: Opportunities and Challenges.
Remote. Sens.
Wenwen Li, Chia-Yu Hsu, Marco Tedesco
2024 J jnl
GeoAI Reproducibility and Replicability: a computational and spatial perspective.
CoRR
Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Peter Kedron
2024 J jnl
Geospatial foundation models for image analysis: evaluating and enhancing NASA-IBM Prithvi's domain adaptability.
CoRR
Chia-Yu Hsu, Wenwen Li, Sizhe Wang
2024 J jnl
Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications.
CoRR
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 Arévalo, Wenwen Li, Hamed Alemohammad, Pontus Olofsson, Christopher Hain, Robert Kennedy, Bianca Zadrozny, Gabriele Cavallaro, Campbell D. Watson, Manil Maskey, Rahul Ramachandran, Juan Bernabé-Moreno
2024 J jnl
Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model's Generalizability in Permafrost Mapping.
CoRR
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
2024 J jnl
Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model's Generalizability in Permafrost Mapping.
Remote. Sens.
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
2023 J jnl
Assessment of IBM and NASA's geospatial foundation model in flood inundation mapping.
CoRR
Wenwen Li, Hyunho Lee, Sizhe Wang, Chia-Yu Hsu, Samantha T. Arundel
2023 — conf
Assessment of a new GeoAI foundation model for flood inundation mapping.
GeoAI@SIGSPATIAL
Wenwen Li, Hyunho Lee, Sizhe Wang, Chia-Yu Hsu, Samantha T. Arundel
2023 J jnl
Correction to: GeoImageNet: a multi-source natural feature benchmark dataset for GeoAI and supervised machine learning.
GeoInformatica
Wenwen Li, Sizhe Wang, Samantha T. Arundel, Chia-Yu Hsu
2023 J jnl
Explainable GeoAI: Can saliency maps help interpret artificial intelligence's learning process? An empirical study on natural feature detection.
CoRR
Chia-Yu Hsu, Wenwen Li
2023 J jnl
Explainable GeoAI: can saliency maps help interpret artificial intelligence's learning process? An empirical study on natural feature detection.
Int. J. Geogr. Inf. Sci.
Chia-Yu Hsu, Wenwen Li
2023 J jnl
GeoImageNet: a multi-source natural feature benchmark dataset for GeoAI and supervised machine learning.
GeoInformatica
Wenwen Li, Sizhe Wang, Samantha T. Arundel, Chia-Yu Hsu
2023 J jnl
Real-time GeoAI for High-resolution Mapping and Segmentation of Arctic Permafrost Features.
CoRR
Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Chandi Witharana, Anna Liljedahl
2022 J jnl
GeoAI for Large-Scale Image Analysis and Machine Vision: Recent Progress of Artificial Intelligence in Geography.
ISPRS Int. J. Geo Inf.
Wenwen Li, Chia-Yu Hsu
2022 — conf
Real-time GeoAI for high-resolution mapping and segmentation of arctic permafrost features: the case of ice-wedge polygons.
GeoAI@SIGSPATIAL
Wenwen Li, Chia-Yu Hsu, Sizhe Wang, Chandi Witharana, Anna Liljedahl
2021 J jnl
Knowledge-Driven GeoAI: Integrating Spatial Knowledge into Multi-Scale Deep Learning for Mars Crater Detection.
Remote. Sens.
Chia-Yu Hsu, Wenwen Li, Sizhe Wang
2021 J jnl
Learning from Counting: Leveraging Temporal Classification for Weakly Supervised Object Localization and Detection.
CoRR
Chia-Yu Hsu, Wenwen Li
2020 J jnl
Automated terrain feature identification from remote sensing imagery: a deep learning approach.
Int. J. Geogr. Inf. Sci.
Wenwen Li, Chia-Yu Hsu
2020 A conf
Learning from Counting: Leveraging Temporal Classification for Weakly Supervised Object Localization and Detection.
BMVC
Chia-Yu Hsu, Wenwen Li
2017 — conf
Recognizing terrain features on terrestrial surface using a deep learning model: an example with crater detection.
GeoAI@SIGSPATIAL
Wenwen Li, Bin Zhou, Chia-Yu Hsu, Yixing Li, Fengbo Ren