224 datasets found

The dataset consists of six formal target languages defined for training and testing purposes. Each language is a subset of the alphabet {a, b, c, d}.

Membership-Invariant Subspace Training (MIST) is a method for training classifiers that acts as a defense designed to specifically defend against black-box membership inference...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors examined state-of-the-art attacks of various kinds.

The ALARM method is a fully automated liver attenuation estimation method that combines deep convolutional neural network (DCNN) and morphological operations.

MRI images of knee joint for cartilage defect diagnosis

Fashion-MNIST, KMNIST, CIFAR10, CIFAR100, MNIST, STL10, SVHN

The dataset used in the paper is a suite of 16 real benchmarks for deep learning and image processing applications.

Computational cytometer based on magnetically modulated coherent imaging and deep learning

A new approach to a value network architecture for the game Go, called a multi-labelled (ML) value network. The ML value network has the three advantages, offering different...

CeBed is a benchmark for deep data-driven OFDM channel estimation.

Claims data from two US health systems with a general patient population and diverse payer mixes.

Typical large-scale recommender systems use deep learning models that are stored on a large amount of DRAM. These models often rely on embeddings, which consume most of the...

Quality control stress test for deep learning-based diagnostic model in digital pathology.

MERCURY accelerates DNN training by exploiting input similarity.

A dataset for ECG delineation and a self-trained method for improving the quality of fiducial points prediction within an ECG record.

Magnetic Resonance Fingerprinting (MRF) dataset for tissue parameter estimation

A LoRa dataset collected from 50 Pycom devices, and analyzed the performance of CNN-based RF fingerprinting on short- and long-term variations.

A large-scale WiFi 802.11b dataset, collected from 50 Pycom devices, and analyzed the performance of CNN-based RF fingerprinting on short- and long-term variations using LoRa...

Zenkai is an open-source framework designed to give researchers more control and flexibility over building and training deep learning machines.

The dataset used for energy reconstruction in TAIGA-IACT images using deep learning methods.