564 datasets found

A dataset of images with pothole annotations from various sources, including Google Earth Pro, AUTOPILOT videos, and GoPro camera images.

Vestibular schwannoma growth prediction from longitudinal MRI by time-conditioned neural fields

Training neural networks on image datasets generally require extensive experimentation to find the optimal learning rate regime.

The dataset used in the paper is a pre-trained ResNet-50 classifier, which is used for image synthesis, unpaired image-to-image translation, and feature similarity estimation.

The cardiac dataset is a dataset of MRI images acquired from 100 subjects, with 10 images per subject, using 32 channels and 3T MRI scanner.

A deep learning approach for breast cancer detection on screening mammography.

A survey of the foundations, selected improvements, and some current applications of Deep Convolutional Neural Networks (CNNs).

The dataset used in the paper is the Imagenet dataset, which is a large annotated dataset of images used for image classification tasks.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used DeiT and ViT models on ImageNet-1k and CIFAR-100 datasets.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used DeiT and ViT models on ImageNet-1k and CIFAR-100 datasets.

The proposed system is composed of three neural networks (NN): an auto-regressive module (ARM) fψ, an upsampler fυ and a synthesis fθ.

The dataset used in this paper for low precision deep learning operators.

Binary images are simple — two possible pixel-valued signals with a single channel. The simplicity of binary images has a significant advantage compared to colored and gray...

Video anomaly detection is a challenging task not only because it involves solving many sub-tasks such as motion representation, object localization and action recognition, but...

The dataset used in the paper is the NAS-Bench-201 dataset, which is a benchmark for neural architecture search.

The U-net is a deep convolutional neural network for biomedical image segmentation.

The proposed non-local adaptive loop filter for HEVC.

The proposed MIF approach enhances the quality of each encoded frame leveraging multiple adjacent frames.

The dataset used for training and testing the deep learning models for Reynolds-Averaged Navier-Stokes simulations of airfoil flows.

The VGGFace dataset is a large-scale face recognition dataset containing over 2.6 million images of 9,131 subjects.