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Hybrid Model for White Blood Cell Classification by Mohannad Dawoud is a document available to read on EtoBox.

The study proposes a new hybrid model called Swin Transformer and ConvMixer based Multipath mixer (SC-MP-Mixer) for classifying white blood cells (WBCs) using deep learning techniques. The model combines the strengths of ConvMixer for spatial detail extraction and Swin transformer for long-context feature processing, achieving high accuracy rates of 99.65%, 98.68%, and 95.66% on three different WBC datasets. This approach demonstrates superior classification performance compared to existing state-of-the-art

Author

Mohannad Dawoud

Language

EN