An innovative deep learning framework for skin cancer detection employing ConvNeXtV2 and focal self-attention mechanisms

Research article (Results in Engineering, 2024) · cited 88× · AI/ML
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An innovative deep learning framework for skin cancer detection employing ConvNeXtV2 and focal self-attention mechanisms

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An innovative deep learning framework for skin cancer detection employing ConvNeXtV2 and focal self-attention mechanisms is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). An innovative deep learning framework for skin cancer detection employing ConvNeXtV2 and focal self-attention mechanisms. Retrieved May 24, 2026, from https://4ort.xyz/entity/an-innovative-deep-learning-framework-for-skin-cancer-detection-employing-convnextv2-and-focal-self-attention-mechanisms
MLA “An innovative deep learning framework for skin cancer detection employing ConvNeXtV2 and focal self-attention mechanisms.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/an-innovative-deep-learning-framework-for-skin-cancer-detection-employing-convnextv2-and-focal-self-attention-mechanisms.
BibTeX @misc{4ortxyz_an-innovative-deep-learning-framework-for-skin-cancer-detection-employing-convnextv2-and-focal-self-attention-mechanisms_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{An innovative deep learning framework for skin cancer detection employing ConvNeXtV2 and focal self-attention mechanisms}}, year = {2026}, url = {https://4ort.xyz/entity/an-innovative-deep-learning-framework-for-skin-cancer-detection-employing-convnextv2-and-focal-self-attention-mechanisms}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): An innovative deep learning framework for skin cancer detection employing ConvNeXtV2 and focal self-attention mechanisms — https://4ort.xyz/entity/an-innovative-deep-learning-framework-for-skin-cancer-detection-employing-convnextv2-and-focal-self-attention-mechanisms (retrieved 2026-05-24)

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