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.
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.
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.
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.
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.
test
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.
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
Information:
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
The orchid flower dataset was selected from the northern part of Thailand. The dataset contains Thai native orchid flowers, and each class contains at least 20 samples. The orchid dataset including 52 species and the visual characteristics of the flower are varying in terms of shape, color, texture, size, and the other parts of the orchid plant like a leaf, inflorescence, roots, and surroundings. All images are taken from many devices such as a digital camera, a mobile phone, and other equipment. The orchids dataset contains 3,559 images from 52 categories.
