Rice Mapping in Training Sample Shortage Regions Using a Deep Semantic Segmentation Model Trained on Pseudo-Labels
Summary
Rice Mapping in Training Sample Shortage Regions Using a Deep Semantic Segmentation Model Trained on Pseudo-Labels is a scholarly article[1].
Key Facts
Rice Mapping in Training Sample Shortage Regions Using a Deep Semantic Segmentation Model Trained on Pseudo-Labels's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Rice Mapping in Training Sample Shortage Regions Using a Deep Semantic Segmentation Model Trained on Pseudo-Labels. Retrieved May 24, 2026, from https://4ort.xyz/entity/rice-mapping-in-training-sample-shortage-regions-using-a-deep-semantic-segmentation-model-trained-on-pseudo-labels
MLA“Rice Mapping in Training Sample Shortage Regions Using a Deep Semantic Segmentation Model Trained on Pseudo-Labels.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/rice-mapping-in-training-sample-shortage-regions-using-a-deep-semantic-segmentation-model-trained-on-pseudo-labels.
BibTeX@misc{4ortxyz_rice-mapping-in-training-sample-shortage-regions-using-a-deep-semantic-segmentation-model-trained-on-pseudo-labels_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Rice Mapping in Training Sample Shortage Regions Using a Deep Semantic Segmentation Model Trained on Pseudo-Labels}}, year = {2026}, url = {https://4ort.xyz/entity/rice-mapping-in-training-sample-shortage-regions-using-a-deep-semantic-segmentation-model-trained-on-pseudo-labels}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Rice Mapping in Training Sample Shortage Regions Using a Deep Semantic Segmentation Model Trained on Pseudo-Labels — https://4ort.xyz/entity/rice-mapping-in-training-sample-shortage-regions-using-a-deep-semantic-segmentation-model-trained-on-pseudo-labels (retrieved 2026-05-24)
