DIVERSITY-BASED TWO-PHASE PRUNING STRATEGY FOR MAXIMIZING IMAGE SEGMENTATION GENERALIZATION WITH APPLICATIONS IN TRANSMISSION ELECTRON MICROSCOPY

Diversity-based two-phase pruning strategy for maximizing image segmentation generalization with applications in transmission electron microscopy

For artificial intelligence applications in transmission electron microscopy (TEM), hardware and computational constraints often obstruct real-time data processing, inflating operational costs, consuming valuable instrument time, and heightening the risk of damage to beam-sensitive specimens, thereby complicating reliable data interpretation.To add

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A Novel Two-Stage DEA Model in Fuzzy Environment: Application to Industrial Workshops Performance Measurement

One of the paramount mathematical methods to compute the general performance of organizations is data envelopment analysis (DEA).Nevertheless, in some cases, the decision-making units (DMUs) have middle values.Furthermore, the conventional DEA models have been originally Foodcover formulated solely for crisp data and cannot handle the problems with

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