1. Activity Recognition from Single Chest-Mounted Accelerometer: The dataset collects data from a wearable accelerometer mounted on the chest. The dataset is intended for Activity Recognition research purposes.
2. Synthetic Control Chart Time Series: This data consists of synthetically generated control charts.
3. Dodgers Loop Sensor: Loop sensor data was collected for the Glendale on ramp for the 101 North freeway in Los Angeles
4. CalIt2 Building People Counts: This data comes from the main door of the CalIt2 building at UCI.
5. Metro Interstate Traffic Volume: Hourly Minneapolis-St Paul, MN traffic volume for westbound I-94. Includes weather and holiday features from 2012-2018.
6. Japanese Vowels: This dataset records 640 time series of 12 LPC cepstrum coefficients taken from nine male speakers.
7. Australian Sign Language signs: This data consists of sample of Auslan (Australian Sign Language) signs. Examples of 95 signs were collected from five signers with a total of 6650 sign samples.
8. Australian Sign Language signs (High Quality): This data consists of sample of Auslan (Australian Sign Language) signs. 27 examples of each of 95 Auslan signs were captured from a native signer using high-quality position trackers
9. Human Activity Recognition from Continuous Ambient Sensor Data: This dataset represents ambient data collected in homes with volunteer residents. Data are collected continuously while residents perform their normal routines.
10. Gesture Phase Segmentation: The dataset is composed by features extracted from 7 videos with people gesticulating, aiming at studying Gesture Phase Segmentation. It contains 50 attributes divided into two files for each video.
11. Crop mapping using fused optical-radar data set: Combining optical and PolSAR remote sensing images offers a complementary data set with a significant number of temporal, spectral, textural, and polarimetric features for cropland classification.