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Squeeze‐and‐excitation attention residual learning of propulsion fault features for diagnosing autonomous underwater vehicles
Research article (Journal of Field Robotics, 2024) · cited 14× · AI/ML
Squeeze‐and‐excitation attention residual learning of propulsion fault features for diagnosing autonomous underwater vehicles
Summary
Squeeze‐and‐excitation attention residual learning of propulsion fault features for diagnosing autonomous underwater vehicles is a scholarly article[1].
Key Facts
Squeeze‐and‐excitation attention residual learning of propulsion fault features for diagnosing autonomous underwater vehicles'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). Squeeze‐and‐excitation attention residual learning of propulsion fault features for diagnosing autonomous underwater vehicles. Retrieved May 24, 2026, from https://4ort.xyz/entity/squeezeandexcitation-attention-residual-learning-of-propulsion-fault-features-for-diagnosing-autonomous-underwater-vehic
MLA“Squeeze‐and‐excitation attention residual learning of propulsion fault features for diagnosing autonomous underwater vehicles.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/squeezeandexcitation-attention-residual-learning-of-propulsion-fault-features-for-diagnosing-autonomous-underwater-vehic.
BibTeX@misc{4ortxyz_squeezeandexcitation-attention-residual-learning-of-propulsion-fault-features-for-diagnosing-autonomous-underwater-vehic_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Squeeze‐and‐excitation attention residual learning of propulsion fault features for diagnosing autonomous underwater vehicles}}, year = {2026}, url = {https://4ort.xyz/entity/squeezeandexcitation-attention-residual-learning-of-propulsion-fault-features-for-diagnosing-autonomous-underwater-vehic}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Squeeze‐and‐excitation attention residual learning of propulsion fault features for diagnosing autonomous underwater vehicles — https://4ort.xyz/entity/squeezeandexcitation-attention-residual-learning-of-propulsion-fault-features-for-diagnosing-autonomous-underwater-vehic (retrieved 2026-05-24)
