SYSTEMS AND METHODS OF MEMORY ALLOCATION FOR NEURAL NETWORKS

    公开(公告)号:US20240403119A1

    公开(公告)日:2024-12-05

    申请号:US18581097

    申请日:2024-02-19

    Applicant: Apple Inc.

    Abstract: A method may include accessing a data processing architecture associated with a neural network to determine dependencies between intermediate data layers of the neural network; obtaining dimensions of the intermediate data layers in the neural network; calculating a minimum number of data storage portions for executing the neural network based on the dependencies; determining a memory allocation size for each respective data storage portion of the data storage portions based on the dimensions and dependencies; allocating memory on a storage device for each data storage portion in accordance with its respective determined memory allocation size.

    Compiling models for dedicated hardware

    公开(公告)号:US11468338B2

    公开(公告)日:2022-10-11

    申请号:US16262809

    申请日:2019-01-30

    Applicant: Apple Inc.

    Abstract: The subject technology provides receiving a neural network (NN) model to be executed on a target platform, the NN model including multiple layers that include operations and some of the operations being executable on multiple processors of the target platform. The subject technology further sorts the operations from the multiple layers in a particular order based at least in part on grouping the operations that are executable by a particular processor of the multiple processors. The subject technology determines, based at least in part on a cost of transferring the operations between the multiple processors, an assignment of one of the multiple processors for each of the sorted operations of each of the layers in a manner that minimizes a total cost of executing the operations. Further, for each layer of the NN model, the subject technology includes an annotation to indicate the processor assigned for each of the operations.

    Method for Improving Temporal Consistency of Deep Neural Networks

    公开(公告)号:US20210073589A1

    公开(公告)日:2021-03-11

    申请号:US16821315

    申请日:2020-03-17

    Applicant: Apple Inc.

    Abstract: Training a network for image processing with temporal consistency includes obtaining un-annotated frames from a video feed. A pretrained network is applied to the first frame of first frame set comprising a plurality of frames to obtain a first prediction, wherein the pretrained network is pretrained for a first image processing task. A current version of the pretrained network is applied to each frame of the first frame set to obtain a first prediction. A content loss term is determined, based on the first prediction and a current prediction for the frame, based on the current network. A temporal consistency loss term is also determined based on a determined consistency of pixels within each frame of the first frame set. The pretrained network may be refined based on the content loss term and the temporal term to obtain a refined network.

    System and method for person reidentification

    公开(公告)号:US10318721B2

    公开(公告)日:2019-06-11

    申请号:US15168275

    申请日:2016-05-31

    Applicant: Apple Inc.

    Abstract: Managing a secure session includes detecting a login event at an electronic device using a first login method to initiate a secure session, capturing an initial image at a same time as the login event, capturing initial sensor data at the same time as the login event, monitoring for changes in the sensor data during the secure session, maintaining the secure session based on the initial sensor data and the monitored changes from the initial sensor data, and during the secure session, permitting access to the electronic device using reidentification.

    System and Method for Person Reidentification

    公开(公告)号:US20170091439A1

    公开(公告)日:2017-03-30

    申请号:US15168275

    申请日:2016-05-31

    Applicant: Apple Inc.

    CPC classification number: G06F21/40 G06F21/32 H04L63/0861 H04W12/06

    Abstract: Managing a secure session includes detecting a login event at an electronic device using a first login method to initiate a secure session, capturing an initial image at a same time as the login event, capturing initial sensor data at the same time as the login event, monitoring for changes in the sensor data during the secure session, maintaining the secure session based on the initial sensor data and the monitored changes from the initial sensor data, and during the secure session, permitting access to the electronic device using reidentification.

    Private Retrieval of Location-Based Information

    公开(公告)号:US20240283632A1

    公开(公告)日:2024-08-22

    申请号:US18421778

    申请日:2024-01-24

    Applicant: Apple Inc.

    CPC classification number: H04L9/008 H04W8/26 H04W12/04

    Abstract: A computing device sends a request for location-based information (LBI) to a server, where the request includes first address information indicative of a geographic area (e.g., where the computing device is located), and an encrypted version of second address information that specifies a sub-region of the geographic area. The second address information is encrypted by a first key not accessible to the server. The first address information is used to select a subset of the LBI stored on the server. The server then performs a privacy protocol such as Private Information Retrieval on the selected subset using the encrypted second address information. This produces an encrypted version of the requested LBI without the server having access to information indicating which item of LBI was requested. The encrypted version of the particular item of LBI is returned to the computing device, where it can be decrypted using a second key.

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