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Identifying Urban Wetlands through Remote Sensing Scene Classification Using Deep Learning: A Case Study of Shenzhen, China
Research article (ISPRS International Journal of Geo-Information, 2022) · cited 21× · AI/ML
Identifying Urban Wetlands through Remote Sensing Scene Classification Using Deep Learning: A Case Study of Shenzhen, China
Summary
Identifying Urban Wetlands through Remote Sensing Scene Classification Using Deep Learning: A Case Study of Shenzhen, China is a scholarly article[1].
Key Facts
Identifying Urban Wetlands through Remote Sensing Scene Classification Using Deep Learning: A Case Study of Shenzhen, China's instance of is recorded as scholarly article[2].
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Identifying Urban Wetlands through Remote Sensing Scene Classification Using Deep Learning: A Case Study of Shenzhen, China. Retrieved May 24, 2026, from https://4ort.xyz/entity/identifying-urban-wetlands-through-remote-sensing-scene-classification-using-deep-learning-a-case-study-of-shenzhen-chin
MLA“Identifying Urban Wetlands through Remote Sensing Scene Classification Using Deep Learning: A Case Study of Shenzhen, China.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/identifying-urban-wetlands-through-remote-sensing-scene-classification-using-deep-learning-a-case-study-of-shenzhen-chin.
BibTeX@misc{4ortxyz_identifying-urban-wetlands-through-remote-sensing-scene-classification-using-deep-learning-a-case-study-of-shenzhen-chin_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Identifying Urban Wetlands through Remote Sensing Scene Classification Using Deep Learning: A Case Study of Shenzhen, China}}, year = {2026}, url = {https://4ort.xyz/entity/identifying-urban-wetlands-through-remote-sensing-scene-classification-using-deep-learning-a-case-study-of-shenzhen-chin}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Identifying Urban Wetlands through Remote Sensing Scene Classification Using Deep Learning: A Case Study of Shenzhen, China — https://4ort.xyz/entity/identifying-urban-wetlands-through-remote-sensing-scene-classification-using-deep-learning-a-case-study-of-shenzhen-chin (retrieved 2026-05-24)
