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A general framework for partial to full image registration. (2022)
Working Paper
MORENO-GARCÍA, C.F. and SERRATOSA, F. 2022. A general framework for partial to full image registration. arXiv [online]. Available from: https://doi.org/10.48550/arXiv.2207.06387

Image registration is a research field in which images must be compared and aligned independently of the point of view or camera characteristics. In some applications (such as forensic biometrics, satellite photography or outdoor scene identification... Read More about A general framework for partial to full image registration..

Two layer ensemble of deep learning models for medical image segmentation. [Preprint] (2021)
Working Paper
DANG, T., NGUYEN, T.T., MCCALL, J., ELYAN, E. and MORENO-GARCÍA, C.F. 2021. Two layer ensemble of deep learning models for medical image segmentation. arXiv [online]. Available from: https://doi.org/10.48550/arXiv.2104.04809

In recent years, deep learning has rapidly become a method of choice for the segmentation of medical images. Deep Neural Network (DNN) architectures such as UNet have achieved state-of-the-art results on many medical datasets. To further improve the... Read More about Two layer ensemble of deep learning models for medical image segmentation. [Preprint].