7 datasets found

The dataset used for training deep neural networks using half-precision floating point numbers.

The proposed method uses the MNIST and CIFAR10 datasets for fully-connected DNNs.

CirCNN is a neural network architecture that uses block-circulant matrices to reduce the number of parameters and computations.

Unitary group convolutions (UGConvs) are a building block for neural networks that combines a group convolution with unitary transforms in feature space.

The VGG-16 and ResNet-50 DNNs are used as victim DNNs in the attack.

The VGG and ResNet DNNs are used as victim DNNs in the attack.

The dataset used in this paper is a MobileNetV2 model, which is a type of deep neural network. The dataset is used to evaluate the performance of the proposed heterogeneous system.