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Breast Cancer
A neural network with single-hidden layer of 64 hidden units and ReLU activations. A prior precision of ε = 1, a minibatch size of 128 and 16 Monte-Carlo samples are used for... -
Deep embedded image clustering with transformer and distribution information
Deep embedded image clustering with transformer and distribution information -
Deep spectral clustering using dual autoencoder network
Deep spectral clustering using dual autoencoder network -
Joint unsupervised learning of deep representations and image clusters
Joint unsupervised learning of deep representations and image clusters -
Unsupervised deep embedding for clustering analysis
Unsupervised deep embedding for clustering analysis -
Deep Embedding Clustering Driven by Sample Stability
Deep embedding clustering algorithm driven by sample stability -
Intracranial Hemorrhage Segmentation
Intracranial hemorrhage segmentation using a deep convolutional model -
ARS: Augmented Reality Semi-automatic-labeling
Two novel datasets are created using the ARS pipeline, one on electromechanical components (industrial scenario) and one on fruits (daily-living scenario). -
Road damage detection and classification using deep neural networks with smart...
A dataset for road damage detection and classification using deep neural networks with smartphone images. -
A Dynamic Domain Adaptation Deep Learning Network for EEG-based Motor Imagery...
This paper presents DADLNet, a dynamic domain adaptation based deep learning network framework for decoding motor imagery tasks. -
Maetschke et al. dataset
The dataset used in this study for glaucoma detection from 3D OCT imaging. -
Bitcoin cryptocurrency transaction network
The Bitcoin cryptocurrency transaction network dataset. -
BFRnet: A deep learning-based MR background field removal method for QSM
A deep learning-based method for background field removal in MRI, specifically for QSM in the brain containing significant pathological susceptibility sources -
In-house measured images
The dataset used in this paper for MR image reconstruction with a deep learned prior. -
Deep segmentation networks predict survival of non-small cell lung cancer
PET-CT images of NSCLC patients who received SBRT at the University of Iowa Hospitals and Clinics were investigated in this study. -
CIFAR10 dataset
The dataset used in this paper is the CIFAR10 dataset, which contains 60,000 32x32 color images in 10 classes, with 6,000 images per class. -
New Normal: Cooperative Paradigm for Covid-19
The proposed scheme uses IoT based health monitoring and CNN based object detection methods to detect social distancing violations and track exposed or infected people. -
ImageNet-32
The ImageNet-32 dataset is a subset of the ImageNet dataset, containing 1,281,167 training samples and 50,000 test samples, distributed across 1,000 labels. -
CIFAR10, CIFAR100, ImageNet
MobileNets, MnasNets, EfficientNets, and ResNets -
IRX-1D: A Simple Deep Learning Architecture for Remote Sensing Classifications
Four remote sensing datasets were used for classification with both small and large training samples.
