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ngoc dung

As seen in: International Journal of Asian Studies, MDPI, Dialnet - Universidad de La Rioja, VIR(Vietnam Investment Review), baodongnai.com.vn

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Ngoài ra, để thỏa mãn niềm đam mê chơi bài ăn tiền của các anh em, nhà cái còn phát triển cổng game bài Topdoithuong365 hoạt động trên tất cả các hệ điều hành như APK, IOS, Android. Điều này giúp người chơi có thể dễ dàng tải về và chơi mọi lúc, mọi nơi. Chi tiết: https://topdoithuong.co/

Articles

Comparison of boosting algorithms for land cover mapping using object-based classification

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By Ngoc Luong, Dinh Vu, Ngọc Dũng, ngoc dung, Thanh Dong Khuc
| Dialnet - Universidad de La Rioja
Ayuda Buscar en la ayuda Buscar en la ayuda Comparison of boosting algorithms for land cover mapping using object-based classification LUONG, Ngoc Dung [1] ; KHUC, Thanh Dong [1] ; VU, Dinh Chieu [1] [1] Hanoi University of Civil Engineering Localización: Revista de teledetección: Revista de la Asociación Española de Teledetección, ISSN 1133-0953, Nº.
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VisRes Bench: On Evaluating the Visual Reasoning Capabilities of VLMs

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By Ngọc Dũng, ngoc dung, Wamiq Reyaz, Phuc Le, Brigitta Malagurski
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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Translational deep learning models for risk stratification to predict prognosis and immunotherapy response in gastric cancer using digital pathology - Journal of Translational Medicine

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By Mai Hanh, Ngọc Dũng, ngoc dung, NGUYÊN THÙY, Nguyen Thi Thuy, Nguyễn Thuỷ, Nguyên Khánh, Nguyễn Khánh
| link.springer.com
Patient selection Our study consisted of hematoxylin and eosin (H&E)-stained formalin-fixed, paraffin-embedded (FFPE) digital slides from The Cancer Genome Atlas (TCGA)-Stomach Adenocarcinoma (STAD). We collected high-resolution pathological images from 292 individuals with clinical information. The diagnostic slides were downloaded in SVS format. Any slides with tissue folds, blurred artifacts, or pen marks were excluded.
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