Artificial Intelligence
Research on damage detection of road surfaces has been an active area of research, but most studies have focused so far on the detection of the presence of damages. However, in real-world scenarios, road managers need to clearly understand the type of damage and its extent in order to take effective action in advance or to allocate the necessary resources. Moreover, currently there are few uniform and openly available road damage datasets, leading to a lack of a common benchmark for road damage detection.
- Categories:
4131 Views
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.
- Categories:
8739 Views
Addtional datasets for the jounal paper subimitted to IEEE Transactions on Computational Imaging, including self-captured light field microscopy datasets with lab-assembled LF microscope.
- Categories:
536 Views
An image dataset including five types of weather conditions (cloudy, sunny, foggy, rainy and snowy) was constructed.
This dataset, called FWID, includes 4000 images for each weather category, leading to a total of 20000 images.
- Categories:
1903 ViewsAn image dataset including five types of weather conditions (cloudy, sunny, foggy, rainy and snowy) was constructed.
This dataset, called FWID, includes 4000 images for each weather category, leading to a total of 20000 images.
- Categories:
482 ViewsAn image dataset including five types of weather conditions (cloudy, sunny, foggy, rainy and snowy) was constructed.
This dataset, called FWID, includes 4000 images for each weather category, leading to a total of 20000 images.
- Categories:
3899 Views
test
- Categories:
69 Views
This dataset was created for research on blockchain anomaly and fraud detection. And donated to IEEE data port online community.
https://github.com/epicprojects/blockchain-anomaly-detection
Files:
bitcoin_hacks_2010_2013.csv: Contains known hashes of bitcoin theft/malicious transactions from 2010-2013
malicious_tx_in.csv: Contains hashes of input transactions flowing into malicious transactions.
- Categories:
4422 Views
Information:
This dataset was created for research on blockchain anomaly and fraud detection. And donated to IEEE data port online community.
Research experiments for this dataset can be found at https://github.com/epicprojects/blockchain-anomaly-detection
- Categories:
5899 Views