434 datasets found

A fine-tuning approach was employed to incorporate information learned from the WMn network to segment thalamic nuclei from CSFn-MPRAGE images, which have poor intra-thalamic...

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...

The dataset consists of 60,000 images of objects in 200 categories, with 300 images per category.

The dataset used in the paper is a collection of neural networks trained on different tasks, including scalar functions, two-dimensional vector fields, and images of a rotating...

Automated segmentation of vertebrae on lateral chest radiography using deep learning

A dataset used for automatic detection and counting of wheat spikelet using semi-automatic labeling and deep learning.

The dataset used in this paper is a collection of received signals of wide beam training and corresponding optimal narrow beam indices.

Protein structures generated by Genie, a novel DDPM for de novo protein design

A new deep learning approach to learn a hierarchy of conditional latent variables that models a population of anatomical segmentations of interest, enables the classification of...

The conventional lottery ticket hypothesis (LTH) claims that there exists a sparse subnetwork within a dense neural network and a proper random initial-ization method called the...

DMLab-30 is a benchmark for multitask reinforcement learning in partially observable environments.

A dataset of 425,896 unique activation functions, created using the PANGAEA search space.

Three benchmark datasets: Act-Bench-CNN, Act-Bench-ResNet, and Act-Bench-ViT, created by training convolutional, residual, and vision transformer architectures from scratch with...

Brain MR dataset for tumor classification and source type classification

The eVED dataset is an extended and enriched version of the Vehicle Energy Dataset (VED), with accurate vehicle trip GPS coordinates and external information such as road speed...

CAwa-NeRF: Instant Learning of Compression-Aware NeRF Features

The dataset used in this paper is a collection of 25 state-of-the-art deep neural networks (DNNs) with different architectures and sizes.

CIFAR-10-S is a dataset that combines error-minimizing and One-Pixel Shortcut (OPS) to craft stronger imperceptible unlearnable examples.

One-Pixel Shortcut (OPS) is a data protection method that perturbs only one pixel in each image.

A multi-level ConvLSTM model for the automatic segmentation of left ventricle myocardium in infarcted porcine cine MR images