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From Trained to Untrained: A Novel Change Detection Framework Using Randomly Initialized Models With Spatial–Channel Augmentation for Hyperspectral Images
Research article (IEEE Transactions on Geoscience and Remote Sensing, 2023) · cited 52× · AI/ML
From Trained to Untrained: A Novel Change Detection Framework Using Randomly Initialized Models With Spatial–Channel Augmentation for Hyperspectral Images
Summary
From Trained to Untrained: A Novel Change Detection Framework Using Randomly Initialized Models With Spatial–Channel Augmentation for Hyperspectral Images is a scholarly article[1].
Key Facts
From Trained to Untrained: A Novel Change Detection Framework Using Randomly Initialized Models With Spatial–Channel Augmentation for Hyperspectral Images's instance of is recorded as scholarly article[2].
References
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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). From Trained to Untrained: A Novel Change Detection Framework Using Randomly Initialized Models With Spatial–Channel Augmentation for Hyperspectral Images. Retrieved May 24, 2026, from https://4ort.xyz/entity/from-trained-to-untrained-a-novel-change-detection-framework-using-randomly-initialized-models-with-spatialchannel-augme
MLA“From Trained to Untrained: A Novel Change Detection Framework Using Randomly Initialized Models With Spatial–Channel Augmentation for Hyperspectral Images.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/from-trained-to-untrained-a-novel-change-detection-framework-using-randomly-initialized-models-with-spatialchannel-augme.
BibTeX@misc{4ortxyz_from-trained-to-untrained-a-novel-change-detection-framework-using-randomly-initialized-models-with-spatialchannel-augme_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{From Trained to Untrained: A Novel Change Detection Framework Using Randomly Initialized Models With Spatial–Channel Augmentation for Hyperspectral Images}}, year = {2026}, url = {https://4ort.xyz/entity/from-trained-to-untrained-a-novel-change-detection-framework-using-randomly-initialized-models-with-spatialchannel-augme}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): From Trained to Untrained: A Novel Change Detection Framework Using Randomly Initialized Models With Spatial–Channel Augmentation for Hyperspectral Images — https://4ort.xyz/entity/from-trained-to-untrained-a-novel-change-detection-framework-using-randomly-initialized-models-with-spatialchannel-augme (retrieved 2026-05-24)
