Manually builds ResNet-18 using basic residual blocks rather than relying on torchvision.models, and adapts the stem layer for 32x32 inputs by removing the initial max pooling, making it an educational reference for understanding ResNet architecture.
PyTorch ResNet-18 implementation with Grad-CAM visualization on CIFAR-10
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