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Chia-Yu Hsu
Chia-Yu Hsu
Research Professional, Arizona State University
Verified email at asu.edu
Title
Cited by
Cited by
Year
Automated terrain feature identification from remote sensing imagery: a deep learning approach
W Li, CY Hsu
International Journal of Geographical Information Science 34 (4), 637-660, 2020
1272020
GeoAI for large-scale image analysis and machine vision: recent progress of artificial intelligence in geography
W Li, CY Hsu
ISPRS International Journal of Geo-Information 11 (7), 385, 2022
902022
Tobler’s First Law in GeoAI: A spatially explicit deep learning model for terrain feature detection under weak supervision
W Li, CY Hsu, M Hu
Annals of the American Association of Geographers 111 (7), 1887-1905, 2021
672021
Recognizing terrain features on terrestrial surface using a deep learning model: An example with crater detection
W Li, B Zhou, CY Hsu, Y Li, F Ren
Proceedings of the 1st Workshop on Artificial Intelligence and Deep Learning …, 2017
502017
Knowledge-driven GeoAI: Integrating spatial knowledge into multi-scale deep learning for Mars Crater detection
CY Hsu, W Li, S Wang
Remote Sensing 13 (11), 2116, 2021
472021
Explainable GeoAI: can saliency maps help interpret artificial intelligence’s learning process? An empirical study on natural feature detection
CY Hsu, W Li
International Journal of Geographical Information Science 37 (5), 963-987, 2023
412023
GeoImageNet: a multi-source natural feature benchmark dataset for GeoAI and supervised machine learning
W Li, S Wang, ST Arundel, CY Hsu
GeoInformatica 27 (3), 619-640, 2023
222023
Assessment of a new GeoAI foundation model for flood inundation mapping
W Li, H Lee, S Wang, CY Hsu, ST Arundel
Proceedings of the 6th ACM SIGSPATIAL International Workshop on AI for …, 2023
18*2023
Segment anything model can not segment anything: Assessing ai foundation model’s generalizability in permafrost mapping
W Li, CY Hsu, S Wang, Y Yang, H Lee, A Liljedahl, C Witharana, Y Yang, ...
Remote Sensing 16 (5), 797, 2024
122024
Advancing arctic sea ice remote sensing with ai and deep learning: opportunities and challenges
W Li, CY Hsu, M Tedesco
Remote Sensing 16 (20), 3764, 2024
10*2024
Learning from Counting: Leveraging Temporal Classification for Weakly Supervised Object Localization and Detection
CY Hsu, W Li
31st British Machine Vision Conference 2020, BMVC 2020, 2020
102020
Real-time GeoAI for high-resolution mapping and segmentation of arctic permafrost features: the case of ice-wedge polygons
W Li, CY Hsu, S Wang, C Witharana, A Liljedahl
Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for …, 2022
9*2022
Geospatial foundation models for image analysis: Evaluating and enhancing NASA-IBM Prithvi’s domain adaptability
CY Hsu, W Li, S Wang
International Journal of Geographical Information Science, 1-30, 2024
72024
GeoAI Reproducibility and Replicability: a computational and spatial perspective
W Li, CY Hsu, S Wang, P Kedron
Annals of the American Association of Geographers 114 (9), 2085-2103, 2024
52024
Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications
D Szwarcman, S Roy, P Fraccaro, ÞE Gíslason, B Blumenstiel, R Ghosal, ...
arXiv preprint arXiv:2412.02732, 2024
12024
STEPNet: A Spatial and Temporal Encoding Pipeline to handle Temporal Heterogeneity in Climate Modeling using AI: A Use Case of Sea Ice Forecasting
S Wang, W Li, CY Hsu
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025
2025
A Multi-Scale Vision Transformer-Based Multimodal Geoai Model for Mapping Arctic Permafrost Thaw
Z Gu, W Li, CY Hsu, S Wang, Y Yang, BM Rogers, A Liljedahl
Available at SSRN 4762408, 0
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