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    Generative interior design in video games
    1.
    发明授权
    Generative interior design in video games 有权

    公开(公告)号：US12220640B2

    公开(公告)日：2025-02-11

    申请号：US17463754

    申请日：2021-09-01

    Applicant: Electronic Arts Inc.

    Inventor： Han Liu ,  Jingwen Liang ,  Schaefer Mitchell ,  Mohsen Sardari

    IPC: A63F13/63 ,  G06F30/12 ,  G06F30/13 ,  G06N3/049

    Abstract: This specification describes a computer-implemented generative interior design method. The method comprises obtaining input data comprising boundary data. The boundary data defines a boundary of an interior region of a video game building. A floor plan for the interior region of the video game building is generated. This comprises processing the input data using a floor plan generator model. The floor plan divides the interior region into a plurality of interior spaces. A layout for at least one of the plurality of interior spaces defined by the floor plan is generated by a layout generator model comprising one or more graph neural networks. The layout represents a configuration of one or more objects to be placed in the interior region.

    Keyframe extractor
    2.
    发明授权
    Keyframe extractor 有权

    公开(公告)号：US12217494B2

    公开(公告)日：2025-02-04

    申请号：US17224034

    申请日：2021-04-06

    Applicant: Gracenote, Inc.

    Inventor： Andreas Schmidt

    IPC: G06V10/82 ,  G06F18/24 ,  G06F18/2413 ,  G06N3/049 ,  G06N3/08 ,  G06V10/80 ,  G06V20/40 ,  H04N21/234 ,  H04N21/81

    Abstract: In one aspect, an example method includes (i) determining a blur delta that quantifies a difference between a level of blurriness of a first frame of a video and a level of blurriness of a second frame of the video, wherein the second frame is subsequent to and adjacent to the first frame; (ii) determining a contrast delta that quantifies a difference between a contrast of the first frame and a contrast of the second frame; (iii) determining a fingerprint distance between a first image fingerprint of the first frame and a second image fingerprint of the second frame; (iv) determining a keyframe score using the blur delta, the contrast delta, and the fingerprint distance; (v) based on the keyframe score, determining that the second frame is a keyframe; and (vi) outputting data indicating that the second frame is a keyframe.

    Transition Detector Neural Network
    3.
    发明申请
    Transition Detector Neural Network 有权

    公开(公告)号：US20250037449A1

    公开(公告)日：2025-01-30

    申请号：US18911726

    申请日：2024-10-10

    Applicant: Gracenote, Inc.

    Inventor： Joseph Renner ,  Aneesh Vartakavi ,  Robert Coover

    IPC: G06V10/82 ,  G06F18/24 ,  G06F18/2413 ,  G06N3/049 ,  G06N3/08 ,  G06V10/80 ,  G06V20/40 ,  H04N21/234 ,  H04N21/81

    Abstract: In one aspect, an example method includes (i) extracting a sequence of audio features from a portion of a sequence of media content; (ii) extracting a sequence of video features from the portion of the sequence of media content; (iii) providing the sequence of audio features and the sequence of video features as an input to a transition detector neural network that is configured to classify whether or not a given input includes a transition between different content segments; (iv) obtaining from the transition detector neural network classification data corresponding to the input; (v) determining that the classification data is indicative of a transition between different content segments; and (vi) based on determining that the classification data is indicative of a transition between different content segments, outputting transition data indicating that the portion of the sequence of media content includes a transition between different content segments.

    Spike timing dependent plasticity write method and synapse array apparatus
    4.
    发明授权
    Spike timing dependent plasticity write method and synapse array apparatus 有权

    公开(公告)号：US12198036B2

    公开(公告)日：2025-01-14

    申请号：US17324062

    申请日：2021-05-18

    Applicant: Winbond Electronics Corp.

    Inventor： Yasuhiro Tomita ,  Masaru Yano

    IPC: G11C11/00 ,  G06N3/049 ,  G06N3/065 ,  G11C13/00

    Abstract: A resistance variable type synapse array apparatus that can perform STDP writing using a positive potential is provided. The synapse array apparatus includes a writing unit writing to a selected resistance variable type memory element in a crossbar array. The writing unit includes a driver generating a positive pulse signal corresponding to a positive part of a spike signal generated by a presynaptic neuron, a driver generating a positive pulse signal corresponding to a negative part of a spike signal generated by a postsynaptic neuron, a driver generating a positive pulse signal corresponding to a positive part of the spike signal generated by the postsynaptic neuron, and a driver generating a positive pulse signal corresponding to a negative part of the spike signal generated by the presynaptic neuron.

    LONG SHORT-TERM MEMORY ANOMALY DETECTION FOR MULTI-SENSOR EQUIPMENT MONITORING
    7.
    发明申请
    LONG SHORT-TERM MEMORY ANOMALY DETECTION FOR MULTI-SENSOR EQUIPMENT MONITORING 有权

    公开(公告)号：US20240403642A1

    公开(公告)日：2024-12-05

    申请号：US18805376

    申请日：2024-08-14

    Applicant: Applied Materials, Inc.

    Inventor： Sima Didari ,  Tianqing Liao ,  Harikrishnan Rajagopal

    IPC: G06N3/08 ,  G06F18/214 ,  G06N3/049

    Abstract: A method includes identifying current sensor data associated with processing of substrates by substrate processing equipment. The method further includes providing the current sensor data as input to a trained machine learning model. The trained machine learning model is trained using training input comprising a first window of time of historical sensor data and target output comprising the first window of time or a second window of time of the historical sensor data to generate the trained machine learning model. The historical sensor data is associated with normal runs of processing of historical substrates by the substrate processing equipment. The method further includes obtaining, from the trained machine learning model, one or more outputs. The method further includes causing, based on the one or more outputs, an anomaly response action associated with the substrate processing equipment.

    Backpropagation of errors in pulsed form in a pulsed neural network
    10.
    发明授权
    Backpropagation of errors in pulsed form in a pulsed neural network 有权

    公开(公告)号：US12147902B2

    公开(公告)日：2024-11-19

    申请号：US17287277

    申请日：2019-10-22

    Applicant: COMMISSARIAT A L'ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES

    Inventor： Johannes Thiele ,  Olivier Bichler

    IPC: G06N3/084 ,  G06N3/048 ,  G06N3/049 ,  G06N3/065

    Abstract: A new implementation is provided for an error back-propagation algorithm that is suited to the hardware constraints of a device implementing a spiking neural network. The invention notably uses binary or ternary encoding of the errors calculated in the back-propagation phase to adapt its implementation to the constraints of the network, and thus to avoid having to use floating-point number multiplication operators. More generally, the invention proposes a global adaptation of the back-propagation algorithm to the specific constraints of a spiking neural network. In particular, the invention makes it possible to use the same propagation infrastructure to propagate the data and to back-propagate the errors in the training phase. The invention proposes a generic implementation of a spiking neuron that is suitable for implementing any type of spiking neural network, in particular convolutional networks.

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