Abstract: As wafer maps become increasingly complex and high-dimensional, conventional clustering methods often fail to uncover subtle but meaningful defect patterns critical for yield enhancement and ...
Proteomic profiling reveals molecular clusters and severity biomarkers in bullous pemphigoid, highlighting disease ...
Urinrinoghene Lauretta Omughelli, a Nigerian cloud infrastructure and artificial intelligence (AI) systems engineer, is ...
Researchers at University of Tsukuba examined the association between sleep characteristics and workplace productivity using ...
Abstract: In football match videos, team affiliation is typically identified using unsupervised methods, which distinguish individuals based on unique features. These methods reduce the effort needed ...
This is an agile repository to perform cell unsupervised clustering using Hibou-L model to extract the cell embeddings. Each embedding has a size of 1024 for which dimensionality reductions is also ...
High temperature oxidation and corrosion degradation mechanisms dictate the lifetime of materials critical to energy production. The combination of modeling and experimental approaches such as machine ...
Clustering is an unsupervised machine learning technique used to organize unlabeled data into groups based on similarity. This paper applies the K-means and Fuzzy C-means clustering algorithms to a ...
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