Sizhe Wang

Sizhe Wang

Arizona State University

H-index: 12

North America-United States

About Sizhe Wang

Sizhe Wang, With an exceptional h-index of 12 and a recent h-index of 12 (since 2020), a distinguished researcher at Arizona State University, specializes in the field of Information Retrieval, Geospatial Data Visualization.

His recent articles reflect a diverse array of research interests and contributions to the field:

Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model’s Generalizability in Permafrost Mapping

Assessment of a new GeoAI foundation model for flood inundation mapping

Assessment of IBM and NASA's geospatial foundation model in flood inundation mapping

GeoImageNet: a multi-source natural feature benchmark dataset for GeoAI and supervised machine learning

Real-time GeoAI for High-resolution Mapping and Segmentation of Arctic Permafrost Features

GeoGraphViz: Geographically constrained 3D force‐directed graph for knowledge graph visualization

Semantic similarity measure of natural language text through machine learning and a keyword‐aware cross‐encoder‐ranking summarizer—A case study using UCGIS GIS &T body of …

Geographvis: a knowledge graph and geovisualization empowered cyberinfrastructure to support disaster response and humanitarian aid

Sizhe Wang Information

University

Position

PhD student of Computer Science

Citations(all)

325

Citations(since 2020)

289

Cited By

77

hIndex(all)

12

hIndex(since 2020)

12

i10Index(all)

13

i10Index(since 2020)

12

Email

University Profile Page

Google Scholar

Sizhe Wang Skills & Research Interests

Information Retrieval

Geospatial Data Visualization

Top articles of Sizhe Wang

Segment Anything Model Can Not Segment Anything: Assessing AI Foundation Model’s Generalizability in Permafrost Mapping

Remote Sensing

2024/1

Assessment of a new GeoAI foundation model for flood inundation mapping

2023/11/13

Assessment of IBM and NASA's geospatial foundation model in flood inundation mapping

arXiv preprint arXiv:2309.14500

2023/9/25

GeoImageNet: a multi-source natural feature benchmark dataset for GeoAI and supervised machine learning

GeoInformatica

2023/7

Real-time GeoAI for High-resolution Mapping and Segmentation of Arctic Permafrost Features

arXiv preprint arXiv:2306.05341

2023/6/8

GeoGraphViz: Geographically constrained 3D force‐directed graph for knowledge graph visualization

Transactions in GIS

2023/6

Sizhe Wang
Sizhe Wang

H-Index: 4

Wenwen Li
Wenwen Li

H-Index: 23

Semantic similarity measure of natural language text through machine learning and a keyword‐aware cross‐encoder‐ranking summarizer—A case study using UCGIS GIS &T body of …

Transactions in GIS

2023/6

Geographvis: a knowledge graph and geovisualization empowered cyberinfrastructure to support disaster response and humanitarian aid

ISPRS International Journal of Geo-Information

2023/3/7

Performance benchmark on semantic web repositories for spatially explicit knowledge graph applications

2022/12/1

Scaling-up deep learning predictions of hydrography from IfSAR data in Alaska

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

2022/8/6

Know, Know Where, KnowWhereGraph: A densely connected, cross-domain knowledge graph and geo-enrichment service stack for applications in environmental intelligence

AI Magazine

2022/3/31

Knowledge-driven GeoAI: Integrating spatial knowledge into multi-scale deep learning for Mars Crater detection

Remote Sensing

2021/5/28

GeoAI in terrain analysis: Enabling multi-source deep learning and data fusion for natural feature detection

Computers, Environment and Urban Systems

2021/11/1

Sizhe Wang
Sizhe Wang

H-Index: 4

Wenwen Li
Wenwen Li

H-Index: 23

GeoNat v1. 0: A dataset for natural feature mapping with artificial intelligence and supervised learning

Transactions in GIS

2020/6

Wenwen Li
Wenwen Li

H-Index: 23

Sizhe Wang
Sizhe Wang

H-Index: 4

See List of Professors in Sizhe Wang University(Arizona State University)

Co-Authors

academic-engine