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Discretised Neutron Diffusion Equation
The dataset used in this paper is a discretised neutron diffusion equation, solved using a convolutional neural network with pre-determined weights. -
Physics-informed ConvNet: Learning Physical Field from a Shallow Neural Network
The dataset used in the paper is a set of physical field observations with noisy data. -
Convolution Kernel Dataset
The dataset used in this paper is a convolution kernel dataset, which is used to train and evaluate the MetaTune cost model. -
Mixconv: Mixed depthwise convolutional kernels
The proposed method, called MixNet, mixes depthwise separable convolutions. -
EfficientNet: Rethinking model scaling for convolutional neural networks
The proposed method, called EfficientNet, rethinks model scaling for convolutional neural networks. -
Driver Distraction Identification with an Ensemble of Convolutional Neural Net...
The AUC Distracted Driver Dataset was used to evaluate the proposed approach. -
NESTA: A Specialized Neural Processing Engine for Efficient Convolutional Neu...
NESTA: a specialized neural processing engine designed for executing learning models in which filter-weights, input-data, and applied biases are expressed in fixed-point format. -
Binary Convolution Dataset
The dataset used in this paper is a binary convolution dataset, where the inputs are binary images and the outputs are the results of the convolution operation. -
U-net: Con-volutional networks for biomedical image segmentation
U-net: Con-volutional networks for biomedical image segmentation. -
Thermal and IR drop analysis using convolutional encoder-decoder networks
Thermal and IR drop analysis using convolutional encoder-decoder networks. -
Learning Multiple Layers of Features from Tiny Images
The CIFAR-10 dataset consists of 60,000 training images and 10,000 test images. Each image is a 32×32 color image.
