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1.发明公开公开(公告)号：US20230259600A1
公开(公告)日：2023-08-17
申请号：US18155408
申请日：2023-01-17
Applicant: QUALCOMM Incorporated
Inventor： Davide BELLI , Bence MAJOR , Amir JALALIRAD , Daniel Hendricus Franciscus DIJKMAN , Fatih Murat PORIKLI
IPC: G06F21/32
CPC classification number: G06F21/32
Abstract: Certain aspects of the present disclosure provide techniques and apparatus for biometric authentication using an anti-spoofing protection model refined using online data. The method generally includes receiving a biometric data input for a user. Features for the received biometric data input are extracted through a first machine learning model. It is determined, using the extracted features for the received biometric data input and a second machine learning model, whether the received biometric data input for the user is authentic or inauthentic. It is determined whether to add the extracted features for the received biometric data input, labeled with an indication of whether the received biometric data input is authentic or inauthentic, to a finetuning data set. The second machine learning model is adjusted based on the finetuning data set.
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公开(公告)号：US20240372636A1
公开(公告)日：2024-11-07
申请号：US18481655
申请日：2023-10-05
Applicant: QUALCOMM Incorporated
Inventor： Aleksandr ERMOLOV , Bence MAJOR , Mohammed Ali Mohammed HIRZALLAH , Srinivas YERRAMALLI , Taesang YOO
Abstract: Certain aspects of the present disclosure provide techniques and apparatus for improved machine learning. A sequence of data records is accessed, each data record comprising wireless channel measurements and inertial measurement unit (IMU) data. Known position information corresponding to at least a first data record is accessed. A first sequence of positions is determined by processing the sets of IMU data and known position information using a forward operation. A second sequence of positions is determined by processing the sets of IMU data and known position information using a backward operation. An IMU adjustment parameter is generated using the first and second sequences of positions. A pseudo-label is generated for a second data record using the IMU adjustment parameter and the sets of IMU data. A machine learning model is trained, using the second data record and the pseudo-label, to predict positions using one or more wireless channel measurements.
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公开(公告)号：US20250159670A1
公开(公告)日：2025-05-15
申请号：US18505984
申请日：2023-11-09
Applicant: QUALCOMM Incorporated
Inventor： Maximilian Wolfgang Martin ARNOLD , Bence MAJOR , Arash BEHBOODI
IPC: H04W72/044
Abstract: A processor-implemented method for beam management using region information and region-specific codebook generation includes receiving a stream of inputs from one or more sensors. A region of a user equipment (UE) is determined using a digital twin that models an environment observed by the network device based on the stream of inputs. The region is determined based on a position of the UE in the environment. A beam estimate is generated based on a codebook selected based on the region.
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4.发明公开公开(公告)号：US20240295661A1
公开(公告)日：2024-09-05
申请号：US18177713
申请日：2023-03-02
Applicant: QUALCOMM Incorporated
Inventor： Amir JALALIRAD , Bence MAJOR , Davide BELLI , Songwon JEE , Himanshu SHAH , William MORRISON
Abstract: A method of determining a position of a device includes obtaining an initial position of the device without using Global Navigation Satellite System (GNSS) satellites. GNSS measurements are taken of radio frequency (RF) signals transmitted by the GNSS satellites. Initial residuals are determined based, at least in part, on GNSS measured distances determined from the at least a portion of the GNSS measurements and expected distances determined from the initial position. Errors of the GNSS measurements based on the RF signals are estimated. An optimization is performed using some of the estimated errors to produce a modified set of residuals, wherein the optimization is further based on H, wherein H represents a matrix with trigonometric functions of a geometry of the GNSS satellites. A cost minimization method of the modified set of residuals and actual geometry of the GNSS satellites (H) to determine an improved position of the device.
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公开(公告)号：US20210255304A1
公开(公告)日：2021-08-19
申请号：US16698870
申请日：2019-11-27
Applicant: QUALCOMM Incorporated
Inventor： Daniel Hendricus Franciscus FONTIJNE , Amin ANSARI , Bence MAJOR , Ravi Teja SUKHAVASI , Radhika Dilip GOWAIKAR , Xinzhou WU , Sundar SUBRAMANIAN , Michael John HAMILTON
IPC: G01S13/60 , G01S7/02 , G01S7/41 , G01S17/931
Abstract: Disclosed are techniques for employing deep learning to analyze radar signals. In an aspect, an on-board computer of a host vehicle receives, from a radar sensor of the vehicle, a plurality of radar frames, executes a neural network on a subset of the plurality of radar frames, and detects one or more objects in the subset of the plurality of radar frames based on execution of the neural network on the subset of the plurality of radar frames. Further, techniques for transforming polar coordinates to Cartesian coordinates in a neural network are disclosed. In an aspect, a neural network receives a plurality of radar frames in polar coordinate space, a polar-to-Cartesian transformation layer of the neural network transforms the plurality of radar frames to Cartesian coordinate space, and the neural network outputs the plurality of radar frames in the Cartesian coordinate space.
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Patent Agency Ranking
公开(公告)号：US20240144087A1
公开(公告)日：2024-05-02
申请号：US18340671
申请日：2023-06-23
Applicant: QUALCOMM Incorporated
Inventor： Fabio Valerio MASSOLI , Ang LI , Shreya KADAMBI , Hao YE , Arash BEHBOODI , Joseph Binamira SORIAGA , Bence MAJOR , Maximilian Wolfgang Martin ARNOLD
CPC classification number: G06N20/00 , H04B7/0695
Abstract: Certain aspects of the present disclosure provide techniques and apparatus for beam selection using machine learning. A plurality of data samples corresponding to a plurality of data modalities is accessed. A plurality of features is generated by, for each respective data sample of the plurality of data samples, performing feature extraction based at least in part on a respective modality of the respective data sample. The plurality of features is fused using one or more attention-based models, and a wireless communication configuration is generated based on processing the fused plurality of features using a machine learning model.
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公开(公告)号：US20210150347A1
公开(公告)日：2021-05-20
申请号：US17098159
申请日：2020-11-13
Applicant: QUALCOMM Incorporated
Abstract: Aspects described herein provide a method of performing guided training of a neural network model, including: receiving supplementary domain feature data; providing the supplementary domain feature data to a fully connected layer of a neural network model; receiving from the fully connected layer supplementary domain feature scaling data; providing the supplementary domain feature scaling data to an activation function; receiving from the activation function supplementary domain feature weight data; receiving a set of feature maps from a first convolution layer of the neural network model; fusing the supplementary domain feature weight data with the set of feature maps to form fused feature maps; and providing the fused feature maps to a second convolution layer of the neural network model.
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公开(公告)号：US20200175286A1
公开(公告)日：2020-06-04
申请号：US16701021
申请日：2019-12-02
Applicant: QUALCOMM Incorporated
Abstract: Methods of processing vehicle sensor information for object detection may include capturing generating a feature map based on captured sensor information, associating with each pixel of the feature map a prior box having a set of two or more width priors and a set of two or more height priors, determining a confidence value of each height prior and each width prior, outputting an indication of a detected object based on a highest confidence height prior and a highest confidence width prior, and performing a vehicle operation based on the output indication of a detected object. Embodiments may include determining for each pixel of the feature map one or more prior boxes having a center value, a size value, and a set of orientation priors, determining a confidence value for each orientation prior, and outputting an indication of the orientation of a detected object based on the highest confidence orientation.
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公开(公告)号：US20250158688A1
公开(公告)日：2025-05-15
申请号：US18505966
申请日：2023-11-09
Applicant: QUALCOMM Incorporated
Inventor： Maximilian Wolfgang Martin ARNOLD , Bence MAJOR , Arash BEHBOODI , Hanno ACKERMANN , Fabio Valerio MASSOLI , Joseph Binamira SORIAGA , Fatih Murat PORIKLI
IPC: H04B7/06
Abstract: A processor-implemented method for multimodal beam management implemented by a network device includes receiving, by the network device, a stream of inputs from one or more sensors. The network device generates a digital twin modeling an environment of a region observed by the one or more sensors. The digital twin includes one or more objects detected based on the stream of inputs. The network device manages a wireless communication signal beam for communicating with at least one user equipment (UE) in the region observed by the one or more sensors based at least in part on the digital twin.
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公开(公告)号：US20250156605A1
公开(公告)日：2025-05-15
申请号：US18506003
申请日：2023-11-09
Applicant: QUALCOMM Incorporated
Inventor： Maximilian Wolfgang Martin ARNOLD , Bence MAJOR , Arash BEHBOODI
IPC: G06F30/27 , G06N3/0464 , H04W64/00
Abstract: A processor-implemented method for learning an antenna offset for perception-aided wireless communication includes receiving a stream of inputs from one or more sensors. A dynamic segmentation mask corresponding to an object observed by the one or more sensors is generated based on the stream of inputs. A trajectory for the one or more sensors is determined based on the dynamic segmentation mask. An antenna position for the object is predicted based on the trajectory.
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