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Dealing With Highly Unbalanced Sidescan Sonar Image Datasets for Deep Learning Classification Tasks

Research article (Global Oceans 2020: Singapore – U.S. Gulf Coast, 2020) · cited 11× · AI/ML
academia openalex:W3156032354
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Dealing With Highly Unbalanced Sidescan Sonar Image Datasets for Deep Learning Classification Tasks

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Dealing With Highly Unbalanced Sidescan Sonar Image Datasets for Deep Learning Classification Tasks is a scholarly article[1].

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  • Dealing With Highly Unbalanced Sidescan Sonar Image Datasets for Deep Learning Classification Tasks's instance of is recorded as scholarly article[2].

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Dealing With Highly Unbalanced Sidescan Sonar Image Datasets for Deep Learning Classification Tasks. Retrieved May 24, 2026, from https://4ort.xyz/entity/dealing-with-highly-unbalanced-sidescan-sonar-image-datasets-for-deep-learning-classification-tasks
MLA “Dealing With Highly Unbalanced Sidescan Sonar Image Datasets for Deep Learning Classification Tasks.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/dealing-with-highly-unbalanced-sidescan-sonar-image-datasets-for-deep-learning-classification-tasks.
BibTeX @misc{4ortxyz_dealing-with-highly-unbalanced-sidescan-sonar-image-datasets-for-deep-learning-classification-tasks_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Dealing With Highly Unbalanced Sidescan Sonar Image Datasets for Deep Learning Classification Tasks}}, year = {2026}, url = {https://4ort.xyz/entity/dealing-with-highly-unbalanced-sidescan-sonar-image-datasets-for-deep-learning-classification-tasks}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Dealing With Highly Unbalanced Sidescan Sonar Image Datasets for Deep Learning Classification Tasks — https://4ort.xyz/entity/dealing-with-highly-unbalanced-sidescan-sonar-image-datasets-for-deep-learning-classification-tasks (retrieved 2026-05-24)

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