Deep-Learning

This data set contains: 

- Training dataset: 271 CT-scans of inner ears used for optimization and training of the model. 

- Validation dataset: 70 CT-scans of inner ears used for external validation. 

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This dataset investigates the suitability of different filters for Learning-Based Motion Magnification (LBMM) and examines the impact of filter parameters on output results. The study finds that the Butterworth filter produces satisfactory results, while the analysis of IIR filters is unsatisfactory due to computational and memory limitations. Additionally, the efficacy of IIR filters for image processing and the reliability of FIR filters are called into question.

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The performance of our designed CHS-GAN on the NKL dataset

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