Robert Boschgmbh

Robert Duerichen

Zhe Feng

Thomas Rocznik

Christian Peters

Shabnam Ghaffarzadegan

Akshay Malhotra

Rudolf Bichler

Attila Reiss

Mirko Ruhs

A system and method is disclosed for classifying time-series data provided to a machine-learning model from a continuous sensor signal. The data may be 'windowed' or “divided” into a smaller data segment using a first stage classifier where an “event of interest” may be identified. The first stage classifier may employ an algorithm that prohibits false negative identifications. The data segment detected as including an event of interest may then be transmitted to a second stage classifier operable to performs a full classification on the data segment. The multi-stage network may require less power and a less complex structure.

System and method for distributed neural networks on edge devices

A method of detecting occupancy in an area includes obtaining, with a processor, an audio sample from an audio sensor and determining, with the processor, feature functional values of a set of selected feature functionals from the audio sample. The determining of the feature functional values includes extracting features in the set of selected feature functionals from the audio sample, and determining the feature functional values of the set of selected features from the extracted features. The method further includes determining, with the processor, occupancy in the area using a classifier based on the determined feature functional values.

System and method for determining occupancy

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Oxford, United Kingdom

Robert Duerichen