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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. -
Automated Thalamic Nuclei Segmentation Using Multi-Planar Cascaded Convolutio...
A cascaded multi-planar scheme with a modified residual U-Net architecture was used to segment thalamic nuclei on conventional and white-matter-nulled (WMn) magnetization... -
Tiny-ImageNet-200
The dataset used in the paper is Tiny-ImageNet-200, which consists of 100k training, 10k validation, and 10k test images of dimensions 64x64x3. -
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. -
Deep Depth From Focus
Depth from focus (DFF) is a highly ill-posed inverse problem because the optimal focal distance is inferred from sharpness measures which fail in untextured areas. Existing... -
Image style transfer using convolutional neural networks
Image style transfer using convolutional neural networks. -
Tubule Segmentation Dataset
The dataset used for tubule segmentation of inhomogeneity images based on convolutional neural networks with fluorescence microscopy correction. -
Camera Model Identification Challenge
A dataset for camera model identification using convolutional neural networks. -
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. -
Ultrafast Image Categorization in Biology and Neural Models
The dataset used to train the VGG 16 model to detect the presence of an animal or an artifact in a scene. -
MNIST Dataset
The MNIST dataset (Lecun et al., 1998), which consists of 60,000 gray-scale images of handwritten digits. Each image has an accompanying label in {0, 1,..., 9}, and is stored as...
