Christopher A. Ramezan

Comparing feature maps generated using UNet-like CNN, 2 Transformer, Mamba, and hybrid architectures for general

This study compares feature maps produced by semantic segmentation architectures using varying combinations of convolutional neural network (CNN), Transformer, and Mamba selective 26 state space (selective SSM) components with a goal of exploring the following question: does correlation or similarity between the genera...