How do CNNs adapt to high-resolution images without exploding computational cost?

CNNs handle high-resolution images using downsampling, patch-based processing, and efficient convolutions like depthwise separable convolutions.

High-resolution images significantly increase computational cost. CNNs address this using early downsampling layers, strided convolutions, and pooling. Advanced architectures also use patch-based processing or divide images into tiles. Efficient convolution techniques like depthwise separable convolutions reduce computation while maintaining accuracy.