An automatic sparse-based deep cascade framework with multilayer representation for detecting breast cancer

Research article (Measurement, 2024) · cited 12× · AI/ML
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An automatic sparse-based deep cascade framework with multilayer representation for detecting breast cancer

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An automatic sparse-based deep cascade framework with multilayer representation for detecting breast cancer is a scholarly article[1].

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  • An automatic sparse-based deep cascade framework with multilayer representation for detecting breast cancer's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). An automatic sparse-based deep cascade framework with multilayer representation for detecting breast cancer. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-automatic-sparse-based-deep-cascade-framework-with-multilayer-representation-for-detecting-breast-cancer
MLA “An automatic sparse-based deep cascade framework with multilayer representation for detecting breast cancer.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-automatic-sparse-based-deep-cascade-framework-with-multilayer-representation-for-detecting-breast-cancer.
BibTeX @misc{4ortxyz_an-automatic-sparse-based-deep-cascade-framework-with-multilayer-representation-for-detecting-breast-cancer_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An automatic sparse-based deep cascade framework with multilayer representation for detecting breast cancer}}, year = {2026}, url = {https://4ort.xyz/entity/an-automatic-sparse-based-deep-cascade-framework-with-multilayer-representation-for-detecting-breast-cancer}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An automatic sparse-based deep cascade framework with multilayer representation for detecting breast cancer — https://4ort.xyz/entity/an-automatic-sparse-based-deep-cascade-framework-with-multilayer-representation-for-detecting-breast-cancer (retrieved 2026-05-24)

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