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Class Boundary Exemplar Selection Based Incremental Learning for Automatic Target Recognition

Research article (IEEE Transactions on Geoscience and Remote Sensing, 2020) · cited 61× · AI/ML
academia openalex:W3004711070
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Class Boundary Exemplar Selection Based Incremental Learning for Automatic Target Recognition

Summary

Class Boundary Exemplar Selection Based Incremental Learning for Automatic Target Recognition is a scholarly article[1].

Key Facts

  • Class Boundary Exemplar Selection Based Incremental Learning for Automatic Target Recognition's instance of is recorded as scholarly article[2].

References

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Class Boundary Exemplar Selection Based Incremental Learning for Automatic Target Recognition. Retrieved May 24, 2026, from https://4ort.xyz/entity/class-boundary-exemplar-selection-based-incremental-learning-for-automatic-target-recognition
MLA “Class Boundary Exemplar Selection Based Incremental Learning for Automatic Target Recognition.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/class-boundary-exemplar-selection-based-incremental-learning-for-automatic-target-recognition.
BibTeX @misc{4ortxyz_class-boundary-exemplar-selection-based-incremental-learning-for-automatic-target-recognition_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Class Boundary Exemplar Selection Based Incremental Learning for Automatic Target Recognition}}, year = {2026}, url = {https://4ort.xyz/entity/class-boundary-exemplar-selection-based-incremental-learning-for-automatic-target-recognition}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Class Boundary Exemplar Selection Based Incremental Learning for Automatic Target Recognition — https://4ort.xyz/entity/class-boundary-exemplar-selection-based-incremental-learning-for-automatic-target-recognition (retrieved 2026-05-24)

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