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Hybrid deep learning for modeling driving behavior from sensor data

Transfer learning was used by training the network to perform a related task, and then using one of the dense layers directly as our feature space for the real task at hand.

Usage based insurance solutions where smartphone sensor data is used to analyze the driver’s behavior are becoming prevalent these days. However, a major shortcoming of most solutions on the market today, is the fact that trips where the user was a passenger, e.g. taxi trips, get included in...

September 25, 2017 Vincent SpruytOtherNo Comment

Deep learning for long-term predictions

At Sentiance, we use machine learning to extract intelligence from smartphone sensor data such as accelerometer, gyroscope and location. We’ve been doing this for quite a while now, and are very proud on our state-of-the-art results regarding sensor based activity detection, map matching, driving behavior, venue mapping and...