Intel Corporation

Apple Inc.

Mi Sun Park

Lei Yang

Shahrokh Shahidzadeh

Shao-Wen Yang

Myung Hwangbo

Jung Woo

Srikathyayani Srikanteswara

Alexander W Min

David Macdara Moloney

Dave A Cavalcanti

Vallabhajosyula S Somayazulu

Omesh Tickoo

Feng Xue

Mohammad Mamunur Rashid

Venkatesan Nallampatti Ekambaram

Maruti Gupta Hyde

Javier Perez-Ramirez

Ravikumar Balakrishnan

Yiting Liao

Addicam V Sanjay

Roya Doostnejad

Cormac Brick

Mikhail T Galeev

Jonathan Byrne

Xiaofan Xu

Scott Thomas

Yeongseon Lee

Alessandro Palla

Yi Lin Chen

Carlos Márquez Rodríguez-Peral

Léonie Raideen Buckley

Dexmont Alejandro Peña Carillo

Luis M Rodríguez Martín De La Sierra

A method can be performed by a first node for determining a parameter of physical (PHY) layer circuitry of a second node. The method can include implementing a cascaded hierarchy of techniques to determine, based on an electrical signal from a second node, a parameter of the PHY layer circuitry of the second node, and causing an antenna of the first node to transmit an electromagnetic wave consistent with the determined parameter.

Feature detection in collaborative radio networks

A machine learning system is provided to enhance various aspects of machine learning models. In some aspects, a substantially photorealistic three-dimensional (3D) graphical model of an object is accessed and a set of training images of the 3D graphical mode are generated, the set of training images generated to add imperfections and degrade photorealistic quality of the training images. The set of training images are provided as training data to train an artificial neural network.

Deep learning system

An embodiment includes at least one computer readable storage medium comprising instructions that when executed enable a system to: receive (a)(i) first radio signal location data for a first object from a radio sensor; and (a)(ii) first visual signal location data for the first object from a camera sensor; perform feature extraction on (b)(i) the first radio signal location data to determine first extracted radio signal features; and (b)(ii) the first visual signal location data to determine first extracted visual signal features; solve a first association problem between the first extracted radio signal features and the first extracted visual signal features to determine first fused location data; and store the first fused location data in the at least one computer readable storage medium. Other embodiments are described herein.

Vision and radio fusion based precise indoor localization

A method for localizing a device. The method is performed by a communication device. The method includes measuring a phase of a signal that the communication device has received from the device, the signal having a first frequency; measuring a phase of at least one further signal that the communication device has received from the device; the at least one further signal having a second frequency, determining a phase pattern of a measured phase versus frequency, pattern matching the phase pattern with each reference phase pattern of a plurality of pre-determined reference phase patterns. Each reference phase pattern is associated with a distance between the communication device and the further communication device. The method further includes determining the distance between the further communication device and the communication device based on the pattern matching.

Communication device and a method for localization

Sensors provisioned on a first device detect a movement of the first device corresponding to the first device changing position within an environment. Location information for the first device is updated based on the position change. A plurality of signals are detected, at the first device, from a second device in the environment, determine, and a distance between the first and second devices is determined based on each of the signals. From the signals, another change in position of the first device within the environment is determined and the location information updated for the first device. The movement is detected at the first device at an instance between two of the plurality of signals, and location information for the first device based on the first position change is updated prior to detection of the later of the two signals in the plurality of signals.

Two-dimensional encounter location detection

An electronic device for visual-saliency driven scene description is described. The electronic device includes a property identifier to identify properties of a target platform. The properties include target platform device type and target platform device count. The electronic device also includes a salient region detector to detect a salient region of an input in response to the target platform device type being a graphical processing unit (GPU) and the target platform device count being above one. The electronic device further includes a description provider to provide a fine-grained scene description for the salient region.

Visual-saliency driven scene description

Embodiments of the present disclosure provide techniques and configurations for a system to manage a home environment. In one instance, an apparatus for managing a home environment may be configured to detect variations in parameters of signals provided by RFID tags disposed in the home environment to monitor the home environment. The apparatus may identify one or more conditions of an area of the home environment in which the RFID tags are disposed, based at least in part on the variations in the one or more parameters and respective locations of the RFID tags in the area of the home environment. The apparatus may select one or more actions, from a plurality of actions associated with the home environment, based at least in part on the identified conditions. The selected actions may be performed to respond to the identified conditions. Other embodiments may be described and/or claimed.

Home environment management method and apparatus

A system for early warning of non-compliance with an established workflow in a work area includes a radio frequency (RF) sensor configured to detect each of a plurality of RF signals located within the work area, and a monitoring system operably connected to the RF sensor. The monitoring system is configured to compare a temporal sequence of detected RF signals to a predetermined temporal sequence of the RF signals associated with the established workflow, and to determine whether a warning condition exists based on the comparison. The RF signals can be emitted by RFID tags within the work area, such as a patient room of a healthcare provider, and the RFID tags may be associated with a hand sanitizing station, an intravenous solution dispenser, and a healthcare provider staff member, each of which play a role in reducing the incidence of hospital-acquired infections through compliance with corresponding patient safety protocols.

Early warning of non-compliance with an established workflow in a work area

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Hillsboro, OR, United States of America

Mi Sun Park