HDF5
LSD4WSD: Learning SAR Dataset for Wet Snow Detection.
The dataset can be found at : https://zenodo.org/record/8111485
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The Phoenix Contact Relay (PCR) dataset is provided for the development of algorithms for the analysis of lifetime data. It differs from previously published datasets in the number and complexity of measurements, as well as the scope of units tested and the practical relevance of the data. Thus, it provides an opportunity to develop and evaluate new concepts for predictive maintenance. The PCR data set presented includes the life data of 546 relays with a total of more than 106 million switching cycles, collected over a period of several years at a sampling rate of 10 kHz.
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We conducted a massive MIMO channel measurement experiment in an indoor setting on the Rice University campus. We used a 64-antenna RENEW software-defined massive MIMO base station and seven software-defined clients in a large open area inside a building hall. We fixed six of the clients in a circle,15maway from the base station. The seventh node was placed on a robot where we moved the robot across the hall starting from the location of the first client to the last. We moved the robot along the path with different speeds, i.e. with0.5m/s,1m/s, and2m/s.
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Cosmological simulation dataset based on LBNL compressible cosmological hydrodynamics simulation code Nyx (https://ccse.lbl.gov/Research/NYX/). The Nyx simulation data are post-analysis data composed of 3D arrays in space (such as dark matter density, baryon density, temperature, and velocity).
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10 year simulation of GCM plasim on grid of 32x64 and 6 hour resolution
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This repository contains the data related to the paper “CNN-Based Image Reconstruction Method for Ultrafast Ultrasound Imaging” (10.1109/TUFFC.2021.3131383). It contains multiple datasets used for training and testing, as well as the trained models and results (predictions and metrics). In particular, it contains a large-scale simulated training dataset composed of 31000 images for the three different imaging configuration considered (i.e., low quality, high quality, and ultrahigh quality).
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The Jackal UGV, from Clearpath Robotics, was used as the data collecting platform. This skid-steer four-wheel-drive vehicle comes with an onboard IMU, two DC motors with encoders that measure wheel angular speeds, and current sensors that measure motor current outputs. On each side of the robot, the front wheel and back wheel are jointed with a gearbox and so spin together at the same rate and direction. The IMU provided vehicle attitude measurements in terms of Euler angles, as well as linear acceleration and angular rate of the vehicle body in three Euclidean axes.
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KROCO is an acronym for Kinesthetic Robot Contacts. The dataset consists of Learning from Demonstration (LfD, aka Programming by Demonstration (PbD)) samples that were collected via kinesthetic teaching. Each labeled sample is a contact-based (force-based) interaction with the environment.
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