Introduction This project implements an optimized ResNet architecture with Squeeze-and-Excitation (SE) blocks to enhance feature learning. The model is trained on the CIFAR-10 dataset, leveraging ...

In the paper, we introduce a bipolar morphological ResNet (BM-ResNet) model obtained from a much more complex ResNet architecture by converting its layers to bipolar morphological ones. We apply ...

Also, we present an ITL-based analysis of the residual network (ResNet) architecture and propose an explanation for why the identity mapping is the optimal shortcut connection. Published in: 2022 ...

Model Architecture (v1) The ResNet model used in this project consists of multiple convolutional layers followed by residual blocks and fully connected layers. The architecture is defined in ...