1. banknote authentication: Data were extracted from images that were taken for the evaluation of an authentication procedure for banknotes.
2. Wireless Indoor Localization: Collected in indoor space by observing signal strengths of seven WiFi signals visible on a smartphone. The decision variable is one of the four rooms.
3. Character Trajectories: Multiple, labelled samples of pen tip trajectories recorded whilst writing individual characters. All samples are from the same writer, for the purposes of primitive extraction. Only characters with a single pen-down segment were considered.
4. Rice (Cammeo and Osmancik): A total of 3810 rice grain's images were taken for the two species, processed and feature inferences were made. 7 morphological features were obtained for each grain of rice.
5. 2.4 GHZ Indoor Channel Measurements: Measurement of the S21,consists of 10 sweeps, each sweep contains 601 frequency points with spacing of 0.167MHz to cover a 100MHz band centered at 2.4GHz.
6. Occupancy Detection : Experimental data used for binary classification (room occupancy) from Temperature,Humidity,Light and CO2. Ground-truth occupancy was obtained from time stamped pictures that were taken every minute.
7. BLE RSSI dataset for Indoor localization: This dataset contains RSSIs obtained on smartphones(Sony Xperia XA1). Signals were transmitted from BLE product called iTAG. Location column denotes the position of iTAG in building's entry.
8. Skin Segmentation: The Skin Segmentation dataset is constructed over B, G, R color space. Skin and Nonskin dataset is generated using skin textures from face images of diversity of age, gender, and race people.