Shypd.aiThe largest open index of AI toolsAdderNet is an AI Frameworks & Infra tool that replaces multiplications in deep neural networks with additions to reduce computation costs. It achieves high accuracy on ImageNet and CIFAR datasets without multiplications in convolution layers.
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AdderNet is an innovative AI framework designed to significantly reduce computation costs in deep neural networks, particularly convolutional neural networks (CNNs), by replacing traditional multiplications with more efficient additions. This is achieved by using the L1-norm distance between filters and input features as the output response. The framework demonstrates impressive performance, achieving 74.9% Top-1 accuracy and 91.7% Top-5 accuracy using ResNet-50 on the ImageNet dataset, all without any multiplication operations in the convolution layer. It also shows strong classification results on CIFAR-10 and CIFAR-100 datasets, as well as competitive super-resolution and adversarial robustness benchmarks. The project provides code for training and evaluation on these datasets, making it a valuable resource for researchers and developers focused on efficient deep learning.
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