564 datasets found

The dataset used in this paper is a collection of neural network acceleration with TensorFlow and FPGA.

The METABRIC dataset contains clinical data for breast cancer patients, including features and event times.

The Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments provides information about 8873 seriously ill hospitalized adults with 14 features...

The CASIA ITDE v.2 dataset is a binary classification dataset that differentiates between authentic and tampered images.

A dataset for Deep Convolutional Neural Network for Inverse Problems in Imaging

Human pose estimation refers to the task of recognizing postures by localizing body keypoints (head, shoulders, elbows, wrists, knees, ankles, etc.) from images.

A hierarchical generative network for vector graphics animation.

Remote sensing image classification benchmark (RSI-CB) based on massive, scalable, and diverse crowdsource data.

TREC 2019 and TREC 2020 Deep Learning Track datasets

The dataset used in the paper is ResNet-20, a deep convolutional neural network for image classification.

The dataset used in the paper is MNIST, CIFAR10 and STL10. These are datasets for image classification tasks.

q-Space Deep Learning for Twelve-Fold Shorter and Model-Free Diffusion MRI Scans.

DELIMIT is a framework extension for deep learning in dif-fusion imaging, which extends the basic framework PyTorch towards spherical signals.

A deep learning and IoT based computer vision system to process computer vision and natural language in real time in order to address the safety and security of production sites...

Brain tumors present a grave risk to human life, demanding precise and timely diagnosis for effective treatment. Inaccurate identification of brain tumors can significantly...

The dataset used in the paper to prove the representation defects of a cascaded convolutional decoder network in frequency representation.

Medical head CT-scan imaging has been successfully combined with deep learning for medical diagnostics of head diseases and lesions. A custom dataset was used for this study.

Audio-Visual Segmentation (AVS) aims to extract the sounding object from a video frame, which is represented by a pixel-wise segmentation mask for application scenarios such as...

QuadConv: Quadrature-based convolutions with applications to non-uniform PDE data compression.

The dataset used in the paper is a graph neural network (GNN) dataset, where the goal is to learn a GNN with one hidden layer for node information convolution.