Machine Learning

2020 IEEE GRSS Data Fusion Contest

The 2020 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS) and the Technical University of Munich, aims to promote research in large-scale land cover mapping based on weakly supervised learning from globally available multimodal satellite data. The task is to train a machine learning model for global land cover mapping based on weakly annotated samples.

Artificial Intelligence

Machine Learning

Image Fusion

Geoscience and Remote Sensing

Submitted On:

Tue, 12/10/2019 - 00:59

Last Updated On:

Mon, 01/25/2021 - 09:03

GPS data collected from "Xinda" autonomous vehicle of Chang'an University

The file 'GPS_P2.zip' is the dataset collected from the GNSS sensor of "Xinda" autonomous vehicle in the Connected Autonomous Vehicles Test Fields (the CAVs Test Fields) Weishui Campus,Chang'an University.

The file 'fault.zip' is the simulated faults in the healthy data in '.mat' format, where X_abrupt, X_noise and X_drift represent abrupt faults, noise and drift in the long run are added into the healthy data, respectively.

Categories:: Machine Learning
Transportation
Sensors

1311 Views

Heidelberg Spiking Datasets

The Heidelberg Spiking Datasets comprise two spike-based classification datasets: The Spiking Heidelberg Digits (SHD) dataset and the Spiking Speech Command (SSC) dataset. The latter is derived from Pete Warden's Speech Commands dataset (https://arxiv.org/abs/1804.03209), whereas the former is based on a spoken digit dataset recorded in-house and included in this repository. Both datasets were generated by applying a detailed inner ear model to audio recordings. We distribute the input spikes and target labels in HDF5 format.

Categories:: Machine Learning

2514 Views

Dataset for electronic nose from various beef cuts

The development of electronic nose (e-nose) for a rapid, simple, and low-cost meat assessment system becomes the concern of researchers in recent years. Hence, we provide time-series datasets that were recorded from e-nose for beef quality monitoring experiment. This dataset is originated from 12 type of beef cuts including round (shank), top sirloin, tenderloin, flap meat (flank), striploin (shortloin), brisket, clod/chuck, skirt meat (plate), inside/outside, rib eye, shin, and fat.

Categories:: IoT
Machine Learning
Sensors
Signal Processing

1591 Views

Brain Signals and the Corresponding Hand Movement Signals Dataset (BS-HMS-Dataset)

BS-HMS-Dataset is a dataset of the users' brainwave signals and the corresponding hand movement signals from a large number of volunteer participants. The dataset has two parts; (1) Neurosky based Dataset (collected over several months in 2016 from 32 volunteer participants), and (2) Emotiv based Dataset (collected from 27 volunteer participants over several months in 2019).

Categories:: Machine Learning
Sensors
Security
Neuroscience
Brain
Wearable Sensing

4012 Views

Detecting XSS attacks by combining CNN with LSTM

Categories:: Machine Learning
Security

2870 Views

Trained NN

Categories:: Machine Learning

171 Views

WiFi RSSI Indoor Localization

A reliable and comprehensive public WiFi fingerprinting database for researchers to implement and compare the indoor localization’s methods.The database contains RSSI information from 6 APs conducted in different days with the support of autonomous robot.