StoHisNet: A hybrid multi-classification model with CNN and Transformer for gastric pathology images
Summary
StoHisNet: A hybrid multi-classification model with CNN and Transformer for gastric pathology images is a scholarly article[1].
Key Facts
StoHisNet: A hybrid multi-classification model with CNN and Transformer for gastric pathology images's instance of is recorded as scholarly article[2].
References
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Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). StoHisNet: A hybrid multi-classification model with CNN and Transformer for gastric pathology images. Retrieved May 24, 2026, from https://4ort.xyz/entity/stohisnet-a-hybrid-multi-classification-model-with-cnn-and-transformer-for-gastric-pathology-images
MLA“StoHisNet: A hybrid multi-classification model with CNN and Transformer for gastric pathology images.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/stohisnet-a-hybrid-multi-classification-model-with-cnn-and-transformer-for-gastric-pathology-images.
BibTeX@misc{4ortxyz_stohisnet-a-hybrid-multi-classification-model-with-cnn-and-transformer-for-gastric-pathology-images_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{StoHisNet: A hybrid multi-classification model with CNN and Transformer for gastric pathology images}}, year = {2026}, url = {https://4ort.xyz/entity/stohisnet-a-hybrid-multi-classification-model-with-cnn-and-transformer-for-gastric-pathology-images}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): StoHisNet: A hybrid multi-classification model with CNN and Transformer for gastric pathology images — https://4ort.xyz/entity/stohisnet-a-hybrid-multi-classification-model-with-cnn-and-transformer-for-gastric-pathology-images (retrieved 2026-05-24)
