80 datasets found

Physics-Informed Neural Networks (PINNs) have received increased interest for forward, inverse, and surrogate modeling of problems described by partial differential equations...

The dataset used in this paper is a simulation framework for turbo encoding and decoding operations. It consists of four autoencoding problems: one for encoding and three for...

A dataset for wireless mobile channel modeling, including ray tracing and deep learning fusion super-resolution modeling method for cluster characteristics prediction.

Copy detection patterns (CDP) are an attractive technology that allows manufacturers to defend their products against counterfeiting. The main assumption behind the protection...

The dataset used in the paper is a collection of expert demonstrations for various tasks, including robotic manipulation, maze navigation, and Atari games.

The dataset used in the paper is a collection of expert demonstrations for various tasks, including robotic manipulation, maze navigation, and Atari games.

Photometric stereo with two images using a self-supervised deep learning framework called DeepPS2.

The DeepSNR detection pipeline uses a novel method for generating an SNR ranking statistic from deep learning classifiers, providing for the first time a foundation for powerful...

A dataset of depth images collected from children under 5 years of age using a smartphone, used for height estimation.

The dataset used for zoom and learn, a method for generalizing deep stereo matching.

The dataset used in the paper "Breaking the Deadly Triad with a Target Network" for training and testing the proposed algorithms.

PrivCirNet: Efficient Private Inference via Block Circulant Transformation

The MNIST dataset is used to demonstrate the clustering capability of the proposed group-sparse autoencoder.

The proposed interpretable CADx framework is devised to provide the diagnostic decision with interpretation in terms of medical descriptions (BI-RADS).

Moving Infants In RGB-D (MINI-RGBD) dataset is used for CP prediction. The dataset contains 12 sequences of real infant movements.

The CIC 2020 dataset is a collection of images with different compression methods.

The dataset used in the paper is a large-scale comparison of pretrained models across computer vision tasks.

The dataset used in this paper is a synthetic dataset of 11940 transmission spectra of exoplanets, generated using the Alfnoor-forward pipeline.

The dataset used in this paper is a dataset of four CNN models: ResNet-18, Vgg-16, Squeezenet v1.0, and AlexNet.

The dataset used in this paper is a convolution kernel dataset, which is used to train and evaluate the MetaTune cost model.