RDCNet reports state-of-the-art accuracy on CIFAR-10, CIFAR-100, SVHN, Imagenette, and Imagewoof by combining random dilated convolutions with multi-branch and attention modules.
Rethinking resnets: Improved stacking strategies with high-order schemes for image clas- sification.Complex and Intelligent Systems, 8(4):3395– 3407, 2022
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Image Classification via Random Dilated Convolution with Multi-Branch Feature Extraction and Context Excitation
RDCNet reports state-of-the-art accuracy on CIFAR-10, CIFAR-100, SVHN, Imagenette, and Imagewoof by combining random dilated convolutions with multi-branch and attention modules.