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Channel Estimation Dataset for RIS-Assisted MIMO Systems
The dataset used in this paper for channel estimation in RIS-assisted MIMO systems. -
SincNet: A Novel CNN Architecture for Speaker Recognition from Raw Waveforms
Speaker recognition is a very active research area with no-table applications in various fields such as biometric authentication, forensics, security, speech recognition, and... -
Smart Device based Initial Movement Detection of Cyclists using Convolutional...
The dataset used for the initial movement detection of cyclists using Convolutional Neural Networks. -
Microstructure-Stress Mapping for Non-Linear Fiber-Reinforced Polymers
A dataset containing 5321 2D microstructure slices sampled from segmented X-ray tomography images of a composite specimen and its corresponding FE simulation. -
Moiré Photo Restoration Using Multiresolution Convolutional Neural Networks
The TIP2018 dataset is a demoiréing dataset, and is used to evaluate the effectiveness of demoiréing methods. -
MNIST-Scale-Local-2 dataset
The MNIST-Scale-Local-2 dataset is created to test the performance of the proposed method on local scale variations. -
MNIST-Scale and FMNIST-Scale datasets
The MNIST-Scale and FMNIST-Scale datasets are used to evaluate the performance of the proposed scale-steerable CNN framework. -
Scale Steerable Filters for Locally Scale-Invariant Convolutional Neural Netw...
The proposed scale-steerable CNN framework is validated on the MNIST-Scale and FMNIST-Scale datasets, which contain global scale variations. Additionally, a synthesized dataset,... -
EvoNet dataset
The dataset used for multiple-image super-resolution reconstruction, combining the advantages of single-image SRR based on deep learning with the benefits of information fusion. -
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...
