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公开(公告)号：US20240171727A1
公开(公告)日：2024-05-23
申请号：US18470326
申请日：2023-09-19
Applicant: QUALCOMM Incorporated
Inventor： Yunxiao SHI , Hong CAI , Fatih Murat PORIKLI , Amin ANSARI , Sai Madhuraj JADHAV
IPC: H04N13/363 , G06T7/50 , G06V10/44 , G06V10/771 , H04N13/351
CPC classification number: H04N13/363 , G06T7/50 , G06V10/44 , G06V10/771 , H04N13/351 , G06V2201/07
Abstract: Systems and techniques are provided for processing image data. For example, a process can include obtaining a plurality of input images associated with a plurality of different spatial views. The process can include generating a set of features based on the plurality of input images. The process can include generating a set of projected features based on the set of features, wherein an embedding size associated with the set of projected features is smaller than an embedding size associated with the set of features. The process can include determining a cross-view attention associated with the plurality of different spatial views, the cross-view attention determined using the set of projected features.
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公开(公告)号：US20230005165A1
公开(公告)日：2023-01-05
申请号：US17808520
申请日：2022-06-23
Applicant: QUALCOMM Incorporated
Inventor： Hong CAI , Janarbek MATAI , Shubhankar Mangesh BORSE , Yizhe ZHANG , Amin ANSARI , Fatih Murat PORIKLI
Abstract: Certain aspects of the present disclosure provide techniques for cross-task distillation. A depth map is generated by processing an input image using a first machine learning model, and a segmentation map is generated by processing the depth map using a second machine learning model. A segmentation loss is computed based on the segmentation map and a ground-truth segmentation map, and the first machine learning model is refined based on the segmentation loss.
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公开(公告)号：US20210208236A1
公开(公告)日：2021-07-08
申请号：US17135545
申请日：2020-12-28
Applicant: QUALCOMM Incorporated
Inventor： Makesh Pravin JOHN WILSON , Amin ANSARI , Sundar SUBRAMANIAN , Volodimir SLOBODYANYUK , Radhika Dilip GOWAIKAR
Abstract: According to some aspects of the disclosure, techniques for compression techniques for the radar data that can be used in real-time applications for automated or self-driving vehicles. One or more compression techniques can be selected and/or configured based on information regarding operational conditions provided by a central (vehicle) computer. Operational conditions can include environmental data (e.g., weather, traffic), processing capabilities, mode of operation, and more. Compression techniques can facilitate transport of compressed radar data from a radar sensor to the central computer for processing of the radar data for object detection, identification, positioning, etc.
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公开(公告)号：US20230185532A1
公开(公告)日：2023-06-15
申请号：US18105159
申请日：2023-02-02
Applicant: QUALCOMM Incorporated
Inventor： Rexford Alan HILL , Aaron Douglass LAMB , Michael GOLDFARB , Amin ANSARI , Christopher LOTT
CPC classification number: G06F7/5443 , G06F5/06 , G06N3/063
Abstract: A method of exploiting activation sparsity in deep neural networks is described. The method includes retrieving an activation tensor and a weight tensor where the activation tensor is a sparse activation tensor. The method also includes generating a compressed activation tensor comprising non-zero activations of the activation tensor, where the compressed activation tensor has fewer columns than the activation tensor. The method further includes processing the compressed activation tensor and the weight tensor to generate an output tensor.
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公开(公告)号：US20220357441A1
公开(公告)日：2022-11-10
申请号：US17316223
申请日：2021-05-10
Applicant: QUALCOMM Incorporated
Inventor： Amin ANSARI , Sundar SUBRAMANIAN , Radhika Dilip GOWAIKAR , Ahmed Kamel SADEK , Makesh Pravin JOHN WILSON , Volodimir SLOBODYANYUK , Shantanu Chaisson SANYAL , Michael John HAMILTON
Abstract: A device for processing image data is disclosed. The device can obtain a radar point cloud and one or more frames of camera data. The device can determine depth estimates of one or more pixels of the one or more frames of camera data. The device can generate a pseudo lidar point cloud using the depth estimates of the one or more pixels of the one or more frames of camera data, wherein the pseudo lidar point cloud comprises a three-dimensional representation of at least one frame of the one or more frames of camera data. The device can determine one or more object bounding boxes based on the radar point cloud and the pseudo lidar point cloud.
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Patent Agency Ranking
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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公开(公告)号：US20200089497A1
公开(公告)日：2020-03-19
申请号：US16134945
申请日：2018-09-18
Applicant: QUALCOMM Incorporated
Inventor： Rakesh KOMURAVELLI , Amin ANSARI , Ramesh Chandra CHAUHAN , Karamvir CHATHA
Abstract: Systems and methods for of minimizing control variance overhead in a dataflow processor include receiving a generating instruction specifying at least an acknowledge predicate based on a first number, a second number, and a first value, wherein a true branch comprises the first number of consumer instructions of the generating instruction based on the first value, used as a first predicate, being true; and a false branch comprises a second number of consumer instructions of the generating instruction based on the first value, used as the first predicate, being false. The acknowledge predicate is evaluated to be a selected number, which is the first number if the first value is true, or the second number if the first value is false. The generating instruction is fired upon the selected number of acknowledge arcs being received from the true branch or the false branch.
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公开(公告)号：US20240200969A1
公开(公告)日：2024-06-20
申请号：US18067798
申请日：2022-12-19
Applicant: QUALCOMM Incorporated
Inventor： Volodimir SLOBODYANYUK , Radhika Dilip GOWAIKAR , Makesh Pravin JOHN WILSON , Shantanu Chaisson SANYAL , Avdhut JOSHI , Christopher BRUNNER , Behnaz REZAEI , Amin ANSARI
CPC classification number: G01C21/3807 , G01C21/3841 , G05B13/027 , G08G1/0104
Abstract: In some aspects, a device may receive sensor data associated with a vehicle and a set of frames. The device may aggregate, using a first pose, the sensor data associated with the set of frames to generate an aggregated frame, wherein the aggregated frame is associated with a set of cells. The device may obtain an indication of a respective occupancy label for each cell from the set of cells, wherein the respective occupancy label includes a first occupancy label or a second occupancy label, and wherein a subset of cells from the set of cells are associated with the first occupancy label. The device may train, using data associated with the aggregated frame, a machine learning model to generate an occupancy grid, based on a loss function that only calculates a loss for respective cells from the subset of cells. Numerous other aspects are described.
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公开(公告)号：US20230086818A1
公开(公告)日：2023-03-23
申请号：US17480570
申请日：2021-09-21
Applicant: QUALCOMM Incorporated
Inventor： Volodimir SLOBODYANYUK , Ahmed Kamel SADEK , Amin ANSARI , Sundar SUBRAMANIAN , Radhika Dilip GOWAIKAR , Makesh Pravin JOHN WILSON , Michael John HAMILTON , Shantanu Chaisson SANYAL
Abstract: System and method for processing a camera frame in a mobile device by partitioning the camera frame into different sections based on the distance from a vehicle to each of the sections and the required resolution of each of the sections. A mobile device comprises: a memory; a processor communicatively coupled to the memory, the processor configured to: receive a camera frame from a camera mounted on a vehicle traveling on a road; determine a drivable path of the vehicle; project the drivable path onto the camera frame; partition a part of the camera frame containing the drivable path into at least one section based on a distance from the vehicle to each of the at least one section; and determine a required resolution of each of the at least one section based on the distance from the vehicle to each of the at least one section.
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公开(公告)号：US20220390582A1
公开(公告)日：2022-12-08
申请号：US17337614
申请日：2021-06-03
Applicant: QUALCOMM Incorporated
Inventor： Volodimir SLOBODYANYUK , Radhika Dilip GOWAIKAR , Makesh Pravin JOHN WILSON , Amin ANSARI , Michael John HAMILTON , Shantanu Chaisson SANYAL , Sundar SUBRAMANIAN
IPC: G01S13/42 , G01S7/03 , G01S13/931
Abstract: In some aspects, a system may receive, from a first one-dimensional radar array, first information based at least in part on first reflections associated with an azimuthal plane. The system may further receive, from a second one-dimensional radar array, second information based at least in part on second reflections associated with an elevation plane. Accordingly, the system may detect an object based at least in part on the first information and may determine an elevation associated with the object based at least in part on the second information. Numerous other aspects are described.
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