
Han Hu
Articles
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Jan 15, 2025 |
nature.com | Hongling Zheng |Li Shen |Anke Tang |Yong Luo |Han Hu |Bo Du | +1 more
AbstractFoundation models have demonstrated remarkable performance across various tasks, primarily due to their abilities to comprehend instructions and access extensive, high-quality data. These capabilities showcase the effectiveness of current foundation models and suggest a promising trajectory.
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Jan 2, 2025 |
pubs.rsc.org | Han Hu
Laser-induced carbonization technology towards biomass-derived carbon materials: mechanism, preparation and application Biomass is considered as a desirable carbon source due to its abundance, low cost, environmental friendliness and sustainability. The traditional preparation methods of biomass-derived carbon materials, typically in-furnace pyrolysis, involve tedious and energy-consuming processes and require harsh operation conditions.
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Dec 19, 2024 |
pubs.rsc.org | Han Hu
Laser-induced carbonization technology towards biomass-derived carbon materials: mechanism, preparation and application Biomass is considered as a desirable carbon source due to its abundance, low cost, environmental friendliness and sustainability. The traditional preparation methods of biomass-derived carbon materials, typically in-furnace pyrolysis, are subjected to tedious and energy-consuming processes and require harsh operation condition.
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Oct 23, 2024 |
arxiv.org | Jianyuan Guo |Li Shen |Yong Luo |Han Hu
Open access is only possible with YOUR support. Give to arXiv this week to help keep science open for all.
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Jun 7, 2023 |
onlinelibrary.wiley.com | Liguo Zhang |Haowei Zeng |Yulin Ding |Han Hu
Landslide susceptibility evaluation (LSE) is a critical issue for disaster prevention. Limited by labor cost and observation technology, landslide samples are extremely limited in dense vegetation-covered and remote areas, making the common supervised learning model underfit with limited samples. Therefore, the reliability of analysis results in mountainous areas is low. Transfer learning can achieve reliable assessment without the need for representative samples.
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