Time series anomaly detection
- Anomaly detection
Detection of anomalies in time series of cyclic nature data.
To develop the algorithm our developers have used an algorithm of confidence bands estimation with L2 metrics.
The algorithm was suggested in the article “Confidence bands for time series data” by J. Korpela, K. Puolamaki and A. Gionis.
The mentioned algorithm was modified to track the seasonal factor in time series: for that purpose several variants of data preprocessing were suggested and tested; the cross-validation system for optimum training parameters selection based on the specifics of the client's system was also realized.
To demonstrate the results data visualization was implemented.
Virtual try-on tool for makeup products
The system consists of a face detection and segmentation model and an algorithm that allows recoloring objects without losing their original texture.
Workout helper app
Mobile app for the estimation of proper body positions during the workout.
Model for restoring blurred and pixelated faces in a photo.