Qualcomm Incorporated

Wi-lan Inc.

Qualcomm Technologies, Inc.

An M Chen

Gordon Kent Walker

Ravinder Paul Chandhok

Jangwon Lee

Bruce Collins

Joseph Peter Barone

Kenneth L Stanwood

Israel Jay Klein

Sajith Balraj

George Lin

Binita Gupta

Prasanna Kannan

Nileshkumar Jayendrabhai Parekh

Ajit Chourasia

Vijaya Datta Mayyuri

Thadi Manjunath Nagaraj

Paul Eric Jacobs

Ben Saidi

Muhua Li

Ravinder Paul (Rob) Chandhok

Chung-Chi Tsai

Meng-Lin Wu

Tom Chin

Ashok Mantravadi

Raghuraman Krishnamoorthi

Ajith Tom Payyappilly

Ralph Akram Gholmieh

Ragulan Sinnarajah

Eric Carl Rosen

Nikolai K N Leung

Linbo Li

Jack Brian Steenstra

Raymond T Hsu

Devarshi P Shah

Qiang Gao

Ajit L Jain

Sony Akkarakaran

Jun Wang

Juan Zhang

Carlos Marcelo Dias Pazos

Ranganathan Krishnan

Wesley James Holland

Baaziz Achour

Fatih Murat Porikli

Christopher John Bennett

Qi Xue

Venkata Ravi Kiran Dayana

Ling Hang

Xun Luo

Michael Orlando DeVico

Mark Charlebois

Carlos Marcelo Pazos

Taoufik Tani

James D Coyer

Ying Gao

Jaikanth Krishnaswamy

Yixin Zhu

Shubhankar Mangesh Borse

Michael G O'Keefe

Vikram Yashpal Malhotra

Shijia Pan

Ning Cai

Systems and techniques are described for processing media data and for providing haptic feedback that is customized based on the media data. A media system receives media content to be output using an output device according to media output settings associated with a media output software application. The media content can be associated with an environment that is at least partially generated by the software application, as in a video game. The output device is configured to output different portions of the media content at different times across a period of time. The media system detects a condition associated with the media content at a first time along the period of time. The media system actuates at least one haptic feedback actuator according to a haptic feedback pattern corresponding to the condition.

Systems and methods for haptic feedback effects

Methods, systems, and apparatuses for image segmentation are provided. For example, a computing device may obtain an image, and may apply a process to the image to generate input image feature data and input image segmentation data. Further, the computing device may obtain reference image feature data and reference image classification data for a plurality of reference images. The computing device may generate reference image segmentation data based on the reference image feature data, the reference image classification data, and the input image feature data. The computing device may further blend the input image segmentation data and the reference image segmentation data to generate blended image segmentation data. The computing device may store the blended image segmentation data within a data repository. In some examples, the computing device provides the blended image segmentation data for display.

Apparatus and methods for image segmentation using machine learning processes

A method for managing model updates by a first zone server, associated with a first zone model of a plurality of zone models, includes receiving a global model from a global server associated with the global model. The method also includes transmitting the global model to user equipment (UEs) in a first group of UEs associated with the first zone model. The method further includes receiving, from one or more UEs in the first group, model updates associated with the global model based on transmitting the global model. The method further includes transmitting, to the global server, an average of the model updates received from the one or more UEs. The method also includes updating the global model to generate the first zone model based on the model updates. The method further includes transmitting the first zone model to one or more UEs in the first group.

Zone-based federated learning

Disclosed are systems, apparatuses, processes, and computer-readable media to provide haptic feedback in electronic devices based on contextual awareness. According to some aspects, a method of controlling haptic feedback includes obtaining environmental information indicative of an environment of a computing device from at least one sensor and determining a context associated with the mobile device based on the environmental information. The method may include determining haptic feedback for output by the mobile device based on the context.

Adjusting haptic rendering based on contextual awareness

Systems and techniques are described herein for modifying the scale and/or position of objects in images. For instance, a system can obtain a two-dimensional (2D) input image from a camera and a three-dimensional (3D) representation of the 2D input image. The system can further determine a first portion of the 3D representation of the 2D input image corresponding to a target object in the 2D input image. The system can adjust a pose of the first portion of the 3D representation of the 2D input image corresponding to the target object. The system can further generate a 2D output image having a modified version of the target object based on the adjusted pose of the first portion of the 3D representation of the 2D input image corresponding to the target object to be output on a display.

Image modification techniques

A method for mobility and zone management in zone-based federated learning includes receiving, at a zone management device of multiple zone management devices, a global model from a first network device associated with the global model. Each of the multiple zone management devices is associated with a corresponding zone model of multiple zone models. The zone management device transmits the global model to mobile devices in a first zone associated with the first zone model based on a zone membership. The zone management device receives weights associated with the global model from each mobile device in the first zone. The zone management device updates the first zone model based on the received weights and the zone membership. The zone management device transmits the updated first zone model to each mobile device in the first zone.

Mobility and zone management in zone-based federated learning

A method for managing model updates by a first network device includes receiving, at the first network device associated with a first zone model of multiple zone models, a global model from a second network device associated with the global model. The method also includes transmitting, from the first network device, the global model to user equipment (UEs) in a first group of UEs associated with the first zone model, a different group of UEs associated with each of the plurality of zone models. The method further includes receiving, at the first network device, weights associated with the global model from each UE in the first group. The method still further includes updating, at the first network device, the first zone model based on the received weights. The method also includes transmitting, from the first network device, the updated first zone model to each UE in the first group.

This disclosure provides systems, methods, and apparatus, including computer programs encoded on computer-readable media, for limiting handoffs in cellular networks. In some aspects, a user equipment (UE) may determine a quantity of handoffs that are performed between two or more radio access technologies (RATs) during a time period. The UE may determine whether the quantity of handoffs exceeds a handoff threshold within the time period. The UE may reduce a rate of handoffs when the UE determines that the quantity of handoffs exceeds the handoff threshold within the time period. The UE also may select one of the RATs to camp on and maintain the wireless connection when the UE determines that the quantity of handoffs exceeds the handoff threshold. The UE may determine which RAT to camp on based on handoff count information, handoff total connection time information, or contextual awareness information.

Limiting handoffs between wireless communication networks during a time period

A method of wireless communication by a wireless device calculates a first latency for a first wireless interface using a DNS (domain name service) protocol. The method also calculates a second latency for a second wireless interface using the DNS protocol. The method stores the first latency and the second latency in a database; and selects the first interface or the second interface based on the calculated first latency and second latency.

Interface selection using domain name service (DNS) round trip time (RTT)

An image capture and processing device captures an image. Based on the image and/or one or more additional images, the image capture and processing device generates and outputs guidance for optimizing image composition, image capture settings, and/or image processing settings. The guidance can be generated based on determination of a direction that a subject of the image is facing, based on sensor measurements indicating that a horizon may be skewed, another image of the same scene captured using a wide-angle lens, another image of the same subject, another image of a different subject, and/or outputs of a machine learning model trained using a set of images. The image capture and processing device can automatically apply certain aspects of the generated guidance, such as image capture settings and/or image processing settings.

Automatic camera guidance and settings adjustment

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit a preamble in a direction using beamforming. The UE may receive an echo based at least in part on the preamble transmitted in the direction. The UE may detect a presence of a person based at least in part on a power level associated with the echo satisfying a threshold. Numerous other aspects are described.

Detecting a presence of a person using a preamble and an echo associated with the preamble

A system and method for mapping a combined frequency division duplexing (FDD) Time Division Multiplexing (TDM)/Time Division Multiple Access (TDMA) downlink subframe for use with half-duplex and full-duplex terminals in a communication system. Embodiments of the downlink subframe vary Forward Error Correction (FEC) types for a given modulation scheme as well as support the implementation of a smart antenna at a base station in the communication system. Embodiments of the system are also used in a TDD communication system to support the implementation of smart antennae. A scheduling algorithm allows TDM and TDMA portions of a downlink to efficiently co-exist in the same downlink subframe and simultaneously support full and half-duplex terminals.

Framing for an adaptive modulation communication system

Disclosed are systems, apparatus, devices, methods, computer program media and products, and other implementations, including a method that includes capturing an RGB image of a hand of a person, capturing a near infrared (NIR) image of the hand, and determining geometrical features of the hand based on the captured RGB and NIR images. In some embodiments, determining the geometrical features may include determining from extracted image data for the hand one or more values representative of relative spatial features for the hand such as one or more of, for example an angle between a first pair of two fingers in the extracted image data for the hand, and/or a relative distance or length for a second pair of fingers in the extracted image data for the hand. In some embodiments, the method may further include determining identity of the person based on the determined geometrical features of the hand.

Feature identification using an RGB-NIR camera pair

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Rancho Santa Fe, CA, United States of America

An M Chen