DCNet: Densely Connected Deep Convolutional Encoder–Decoder Network for Nasopharyngeal Carcinoma Segmentation

Research article (Sensors, 2021) · cited 12× · AI/ML
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DCNet: Densely Connected Deep Convolutional Encoder–Decoder Network for Nasopharyngeal Carcinoma Segmentation

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DCNet: Densely Connected Deep Convolutional Encoder–Decoder Network for Nasopharyngeal Carcinoma Segmentation is a scholarly article[1].

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  • DCNet: Densely Connected Deep Convolutional Encoder–Decoder Network for Nasopharyngeal Carcinoma Segmentation's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). DCNet: Densely Connected Deep Convolutional Encoder–Decoder Network for Nasopharyngeal Carcinoma Segmentation. Retrieved May 24, 2026, from https://4ort.xyz/entity/dcnet-densely-connected-deep-convolutional-encoderdecoder-network-for-nasopharyngeal-carcinoma-segmentation
MLA “DCNet: Densely Connected Deep Convolutional Encoder–Decoder Network for Nasopharyngeal Carcinoma Segmentation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/dcnet-densely-connected-deep-convolutional-encoderdecoder-network-for-nasopharyngeal-carcinoma-segmentation.
BibTeX @misc{4ortxyz_dcnet-densely-connected-deep-convolutional-encoderdecoder-network-for-nasopharyngeal-carcinoma-segmentation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{DCNet: Densely Connected Deep Convolutional Encoder–Decoder Network for Nasopharyngeal Carcinoma Segmentation}}, year = {2026}, url = {https://4ort.xyz/entity/dcnet-densely-connected-deep-convolutional-encoderdecoder-network-for-nasopharyngeal-carcinoma-segmentation}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): DCNet: Densely Connected Deep Convolutional Encoder–Decoder Network for Nasopharyngeal Carcinoma Segmentation — https://4ort.xyz/entity/dcnet-densely-connected-deep-convolutional-encoderdecoder-network-for-nasopharyngeal-carcinoma-segmentation (retrieved 2026-05-24)

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