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COVID-19 Detection via Stacked Ensemble Models by oshinsahare2003 is a document available to read on EtoBox.

This paper presents a novel stacked ensemble model for the detection of COVID-19 from chest CT scans, focusing on achieving high recall and accuracy. The model utilizes transfer learning from four pre-trained computer vision architectures and introduces a unique diversity measure to enhance performance. The effectiveness of the proposed model is evaluated across three different CT scan datasets, emphasizing the importance of minimizing false negatives in COVID-19 diagnosis.

Author
oshinsahare2003
Language
EN