625 datasets found

A neural simulator for outfits. Our methodology yields skinned models with Pose Space Deformation through an implicit Physically Based Simulation using deep learning framework.

A suite of 5 large-scale, industry-grade datasets that enable the empirical study of learning-based RF localization and its robustness to macro- and micro-induced distribution...

RadioBench: a suite of 8 learnt localiser nets from the state-of-the-art to study and benchmark their real-world deployability, utilising five novel industry-grade datasets.

A WiFi-based method combined with convolutional neural networks (CNN) to predict heart rate and respiratory rate is proposed. The inputs to the neural network are the amplitude...

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...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors trained their model on the CLIC training dataset.

The dataset used in the study of FingerNet, a deep neural network for fine motor imagery classification using EEG signals.

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.

A survey on 3D object detection in the era of deep neural networks.

The dataset used in this paper for COVID-19 diagnosis from community acquired pneumonia (CAP) in chest computed tomography (CT) images.

The dataset is used for teasing out missing reactions in genome-scale metabolic networks through deep learning.

A large and diverse dataset of high-resolution RGB labelled images to develop and benchmark wheat head detection methods.

The dataset used in the paper is the GEMM (General Matrix Multiplication) dataset, which is used to evaluate the performance of the proposed algorithm.

The dataset used in the paper is the Versal VCK190 ACAP, which is a heterogeneous architecture containing a dual-core ARM Cortex-A72 processor, a dual-core ARM Cortex-R5F...