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Deep Learning Applications on Multitemporal SAR (Sentinel-1) Image Classification Using Confined Labeled Data: The Case of Detecting Rice Paddy in South Korea
Research article (IEEE Transactions on Geoscience and Remote Sensing, 2020) · cited 48× · AI/ML
Deep Learning Applications on Multitemporal SAR (Sentinel-1) Image Classification Using Confined Labeled Data: The Case of Detecting Rice Paddy in South Korea
Summary
Deep Learning Applications on Multitemporal SAR (Sentinel-1) Image Classification Using Confined Labeled Data: The Case of Detecting Rice Paddy in South Korea is a scholarly article[1].
Key Facts
Deep Learning Applications on Multitemporal SAR (Sentinel-1) Image Classification Using Confined Labeled Data: The Case of Detecting Rice Paddy in South Korea's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Deep Learning Applications on Multitemporal SAR (Sentinel-1) Image Classification Using Confined Labeled Data: The Case of Detecting Rice Paddy in South Korea. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-learning-applications-on-multitemporal-sar-sentinel-1-image-classification-using-confined-labeled-data-the-case-of-
MLA“Deep Learning Applications on Multitemporal SAR (Sentinel-1) Image Classification Using Confined Labeled Data: The Case of Detecting Rice Paddy in South Korea.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-learning-applications-on-multitemporal-sar-sentinel-1-image-classification-using-confined-labeled-data-the-case-of-.
BibTeX@misc{4ortxyz_deep-learning-applications-on-multitemporal-sar-sentinel-1-image-classification-using-confined-labeled-data-the-case-of-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep Learning Applications on Multitemporal SAR (Sentinel-1) Image Classification Using Confined Labeled Data: The Case of Detecting Rice Paddy in South Korea}}, year = {2026}, url = {https://4ort.xyz/entity/deep-learning-applications-on-multitemporal-sar-sentinel-1-image-classification-using-confined-labeled-data-the-case-of-}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep Learning Applications on Multitemporal SAR (Sentinel-1) Image Classification Using Confined Labeled Data: The Case of Detecting Rice Paddy in South Korea — https://4ort.xyz/entity/deep-learning-applications-on-multitemporal-sar-sentinel-1-image-classification-using-confined-labeled-data-the-case-of- (retrieved 2026-05-24)
