TrEnD: A transformer‐based encoder‐decoder model with adaptive patch embedding for mass segmentation in mammograms
Summary
TrEnD: A transformer‐based encoder‐decoder model with adaptive patch embedding for mass segmentation in mammograms is a scholarly article[1].
Key Facts
TrEnD: A transformer‐based encoder‐decoder model with adaptive patch embedding for mass segmentation in mammograms's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). TrEnD: A transformer‐based encoder‐decoder model with adaptive patch embedding for mass segmentation in mammograms. Retrieved May 24, 2026, from https://4ort.xyz/entity/trend-a-transformerbased-encoderdecoder-model-with-adaptive-patch-embedding-for-mass-segmentation-in-mammograms
MLA“TrEnD: A transformer‐based encoder‐decoder model with adaptive patch embedding for mass segmentation in mammograms.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/trend-a-transformerbased-encoderdecoder-model-with-adaptive-patch-embedding-for-mass-segmentation-in-mammograms.
BibTeX@misc{4ortxyz_trend-a-transformerbased-encoderdecoder-model-with-adaptive-patch-embedding-for-mass-segmentation-in-mammograms_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{TrEnD: A transformer‐based encoder‐decoder model with adaptive patch embedding for mass segmentation in mammograms}}, year = {2026}, url = {https://4ort.xyz/entity/trend-a-transformerbased-encoderdecoder-model-with-adaptive-patch-embedding-for-mass-segmentation-in-mammograms}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): TrEnD: A transformer‐based encoder‐decoder model with adaptive patch embedding for mass segmentation in mammograms — https://4ort.xyz/entity/trend-a-transformerbased-encoderdecoder-model-with-adaptive-patch-embedding-for-mass-segmentation-in-mammograms (retrieved 2026-05-24)
