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Neural network tool to predict CCS in EB-CFRP strengthened RC
Neural Network (NN) model to predict CCS load. The file contains the weight and bias matrices obtained from the trained NN model. The input field (shaded in blue) can be changed... -
Sensores compatibles CMOS de bajo consumo con procesado eficiente bioinspirad...
Experimental results of the SENSEDGE project. The videos show how the hardware is configured with the Izhikevich model and a demonstration network that executes simultaneously... -
Procesador integrado extendido para la emulación hardware de sistemas neurona...
Resultados experimentales del proyecto XIPHEENS Experimental HEENS execution examples of a network of Leaky Integrate-and-Fire, and Izhikevich neuron models. -
Replication data for: PosGNN: a graph neural network-based multimodal data fu...
This dataset was created within the framework of the 5GSmartFact project (https://www.5gsmartfact.upc.edu/). It contains Ultra-Wideband (UWB) and Inertial Measurement Unit (IMU)... -
Replication Data and Code for: Real-Time Recognition of Multivariate Event-Ba...
This repository contains the source code and processed datasets for a deep learning framework designed to multivariate event-based time series classification applied to monitor... -
Neural network tool to predict CCS in EB-CFRP strengthened RC
Neural Network (NN) model to predict CCS load. The file contains the weight and bias matrices obtained from the trained NN model. The input field (shaded in blue) can be changed... -
Neural-Guided RANSAC for Estimating Epipolar Geometry [Data]
Pre-computed sparse feature correspondences for pairs of images (outdoor and indoor) to reproduce the experiments described in our paper, particularly to train and evaluate... -
DSAC* Visual Re-Localization [Data]
Supplementary training data for visual camera re-localization, particularly rendered depth maps to be used in combination with the MSR 7Scenes dataset, and the Stanford 12Scenes... -
Expert Sample Consensus (ESAC) for Visual Re-Localization [Data]
Supplementary training data for visual camera re-localization, particularly pre-computed scene coordinates to the MSR 7Scenes dataset and the Standford 12Scenes dataset. We also... -
DSAC++ Visual Camera Re-Localization [Data]
Supplementary training data for visual camera re-localization, particularly rendered depth maps to be used in combination with the Cambridge Landmarks dataset. We also provide... -
Differentiable RANSAC (DSAC) for Visual Re-Localization [Data]
Pre-trained models of our camera re-localization method for the MSR 7Scenes dataset. For more information, also see the code documentation: https://github.com/cvlab-dresden/DSAC -
Replication data for "Predicting Transfer Learning Suitability in ANN-based C...
This data repository supports the in review publication titled "Predicting Transfer Learning Suitability in ANN-based Control of FOPDT Industrial Processes" part of the E-TROTLE... -
Differentiable RANSAC (DSAC) for Visual Re-Localization [Data]
Pre-trained models of our camera re-localization method for the MSR 7Scenes dataset. For more information, also see the code documentation: https://github.com/cvlab-dresden/DSAC -
DSAC++ Visual Camera Re-Localization [Data]
Supplementary training data for visual camera re-localization, particularly rendered depth maps to be used in combination with the Cambridge Landmarks dataset. We also provide... -
Expert Sample Consensus (ESAC) for Visual Re-Localization [Data]
Supplementary training data for visual camera re-localization, particularly pre-computed scene coordinates to the MSR 7Scenes dataset and the Standford 12Scenes dataset. We also... -
DSAC* Visual Re-Localization [Data]
Supplementary training data for visual camera re-localization, particularly rendered depth maps to be used in combination with the MSR 7Scenes dataset, and the Stanford 12Scenes... -
Neural-Guided RANSAC for Estimating Epipolar Geometry [Data]
Pre-computed sparse feature correspondences for pairs of images (outdoor and indoor) to reproduce the experiments described in our paper, particularly to train and evaluate... -
TPCOMP: Temporal Point Clouds of a wOrkpiece in the Machining Process
Temporal point clouds sampled from a workpiece in progress using 16 different machining tools. The datasets were created using a machining simulation in the Unit Industrial...
