Nokia Technologies Oy

Omnibuds Ltd

Fahim Kawsar

Akhil Mathur

Nicholas Lane

Mohammed Alloulah

Zoran Radivojevic

Howard C Huang

Anton Isopoussu

Utku Gunay Acer

Marc Van Den Broeck

Sourav Bhattacharya

Chulhong Min

Alessandro Montanari

Alberto Gil Ramos

Andrea Ferlini

A method is provided that includes determining a quality of a data portion of an input sensor data stream based, at least in part, on data of a first data type and determining between, at least, generation of two or more streams of a second, different data type including at least one synthesised data stream of the second data type. Determining between generation of two or more streams of a second, different data type is based, at least in part, on the determined quality. The synthesis is based, at least in part, on the data of the first data type. The method further includes causing generation of at least one stream of the second, different data type based, at least in part, on the determination between generation of two or more streams of the second, different data type.

Sensing

An apparatus comprising means for: receiving information from at least one inertial measurement unit configured to be worn on a user's head; and causing, at least in part, determining facial expression information in dependence on at least the received information.

Detection of facial expressions

Apparatus having at least one reflective surface configured to reflect electromagnetic waves, wherein a reflective response of at least one portion of the reflective surface with respect to the electromagnetic waves is electronically controllable, wherein the apparatus is configured to at least temporarily control the reflective response of the at least one portion of the reflective surface.

Apparatus for reflecting electromagnetic waves and method of operating such apparatus preliminary class

Apparatus comprising at least one movable reflective surface configured to reflect electromagnetic waves and at least one actuator coupled with the at least one movable reflective surface, wherein said at least one actuator is configured to at least temporarily drive a movement of said at least one reflective surface.

Apparatus for reflecting electromagnetic waves and method of operating such apparatus

Methods and systems are disclosed for updating learned models. An embodiment comprises receiving a plurality of data sets representing sensed data from one or more devices and determining, using one or more local learned models, local parameters based on the received data sets. Another operation may comprise generating a combined data set by combining the plurality of data sets and, determining, using one or more local learned models, global parameters based on the combined data set. Another operation may comprise transmitting, to a remote system, the global parameters for determining updated global parameters using one or more global learned models based at least partially on the global parameters, and receiving, from the remote system, the updated global parameters. Another operation may comprise updating the one or more local learned models using both the local parameters and updated global parameters.

Updating learned models

In one embodiment, the method includes obtaining, by a first processing device, energy demand data representative of the energy consumption of respective tasks of a processing pipeline, obtaining, by the first processing device, battery availability data representative of the available energy of the batteries of other respective processing devices, for respective tasks of the processing pipeline, selecting, by the first processing device, one of the processing devices for executing the task, as a function of the energy demand data and the battery availability data, and controlling, by the first processing device, the execution of the respective tasks on the selected processing devices.

Method and devices for processing sensor data by applying one or more processing pipelines to the sensor data

An apparatus comprising means for: using a generative neural network, trained to translate first sensor data to simulated second sensor data, to translate input first sensor data from a first sensor to simulated second sensor data; and providing the simulated second sensor data to a different, specific-task, machine-learning model for processing at least second sensor data.

Growing community of inventors

Cambridge, United Kingdom

Fahim Kawsar