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Federated Learning for Indoor Localization via Model Reliability With Dropout

Research article (IEEE Communications Letters, 2022) · cited 35× · AI/ML
academia openalex:W4293145903
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Federated Learning for Indoor Localization via Model Reliability With Dropout

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Federated Learning for Indoor Localization via Model Reliability With Dropout is a scholarly article[1].

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  • Federated Learning for Indoor Localization via Model Reliability With Dropout's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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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.

APA 4ort.xyz Knowledge Graph. (2026). Federated Learning for Indoor Localization via Model Reliability With Dropout. Retrieved May 24, 2026, from https://4ort.xyz/entity/federated-learning-for-indoor-localization-via-model-reliability-with-dropout
MLA “Federated Learning for Indoor Localization via Model Reliability With Dropout.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/federated-learning-for-indoor-localization-via-model-reliability-with-dropout.
BibTeX @misc{4ortxyz_federated-learning-for-indoor-localization-via-model-reliability-with-dropout_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Federated Learning for Indoor Localization via Model Reliability With Dropout}}, year = {2026}, url = {https://4ort.xyz/entity/federated-learning-for-indoor-localization-via-model-reliability-with-dropout}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Federated Learning for Indoor Localization via Model Reliability With Dropout — https://4ort.xyz/entity/federated-learning-for-indoor-localization-via-model-reliability-with-dropout (retrieved 2026-05-24)

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