Do you agree? Data normalization isn’t the finish line. Harmonization is. Even after basic normalization, datasets can drift ...

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Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

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AI and large language models (LLMs) are transforming industries with unprecedented potential, but the success of these advanced models hinges on one critical factor: high-quality data. Here, I'll ...

Abstract: To address the current problem that the speed of high-speed spinning bodies varies widely and it is difficult to achieve effective speed measurements throughout the entire flight, this ...

The research fills a gap in standardized guidance for lipidomics/metabolomics data analysis, focusing on transparency and reproducibility using R and Python. The approach offers modular, interoperable ...

Do you hava any plans to add data augmentation and stain color normalization function before features extraction? Since stain color normalization is a very computationally intensive and time-consuming ...

Thanks for publishing the code and your execllent work! I have some question about during the normalization before the training and testing why you use same mean and std for both training and testing ...