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Chang Qu

4 papers

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papers

Publications (4)

cs.CV2021

Compound Figure Separation of Biomedical Images with Side Loss

Tianyuan Yao, Chang Qu, Quan Liu +11

Unsupervised learning algorithms (e.g., self-supervised learning, auto-encoder, contrastive learning) allow deep learning models to learn effective image representations from large…

physics.ao-ph2024

YanTian: An Application Platform for AI Global Weather Forecasting Models

Wencong Cheng, Jiangjiang Xia, Chang Qu +4

To promote the practical application of AI Global Weather Forecasting Models (AIGWFM), we have developed an adaptable application platform named 'YanTian'. This platform enhances e…

cs.LG2023

The Compatibility between the Pangu Weather Forecasting Model and Meteorological Operational Data

Wencong Cheng, Yan Yan, Jiangjiang Xia +3

Recently, multiple data-driven models based on machine learning for weather forecasting have emerged. These models are highly competitive in terms of accuracy compared to tradition…

cs.CV2022

Compound Figure Separation of Biomedical Images: Mining Large Datasets for Self-supervised Learning

Tianyuan Yao, Chang Qu, Jun Long +13

With the rapid development of self-supervised learning (e.g., contrastive learning), the importance of having large-scale images (even without annotations) for training a more gene…

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