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    Hyperspectral image compression using a feature extraction model
    64.
    发明授权
    Hyperspectral image compression using a feature extraction model 有权

    公开(公告)号：US12260596B2

    公开(公告)日：2025-03-25

    申请号：US17667151

    申请日：2022-02-08

    Applicant: Apeel Technology, Inc.

    Inventor： Richard Pattison

    IPC: G06T9/00 ,  G06V10/58

    Abstract: A computer implemented method for reducing an amount of memory required to store hyperspectral images of an object include: obtaining tensor data representing a hyperspectral image including a first portion depicting an object and a second portion depicting at least a portion of a surrounding environment where the object is located; identifying a portion of the tensor data representing the hyperspectral image that corresponds to the first portion; providing the identified portion of the tensor data representing the hyperspectral image as an input to a feature extraction model; obtaining one or more matrix structures as output by the feature extraction model based on the feature extraction model processing the identified portion of the tensor data, the one or more matrix structures representing a subset of features extracted from the identified portion of the tensor data; and storing the one or more matrix structures in a memory device.

    Compounds and formulations for protective coatings
    65.
    发明授权
    Compounds and formulations for protective coatings 有权

    公开(公告)号：US12245605B2

    公开(公告)日：2025-03-11

    申请号：US16427219

    申请日：2019-05-30

    Applicant: APEEL TECHNOLOGY, INC.

    Inventor： Carlos Hernandez ,  Chance Holland ,  Stephen Kaun ,  Louis Perez ,  Charles Frazier

    IPC: A23B7/154 ,  A23B7/16 ,  A23L3/3517

    Abstract: Compositions for forming protective coatings can include a first group of compounds, where each compound of the first group is a fatty acid, fatty acid ester, or fatty acid salt having a carbon chain length of at least 14 carbons. The compositions can optionally include a second group of compounds selected from fatty acids, fatty acid esters, fatty acid salts, and combinations thereof, wherein each compound of the second group has a carbon chain length from 7 to 13 carbons. At least some of the compounds of the first group can function as emulsifiers, allowing the composition to be dissolved, suspended, or dispersed in a solvent. At least some of the compounds of the second group can function as wetting agents in order to improve the surface wetting of items to be coated when solutions, suspensions, or colloids that include the compositions are applied to the items.

    ULTRAVIOLET LIGHT AND MACHINE LEARNING-BASED ASSESSMENT OF FOOD ITEM QUALITY
    68.
    发明公开
    ULTRAVIOLET LIGHT AND MACHINE LEARNING-BASED ASSESSMENT OF FOOD ITEM QUALITY 审中-公开

    公开(公告)号：US20230325899A1

    公开(公告)日：2023-10-12

    申请号：US18131532

    申请日：2023-04-06

    Applicant: Apeel Technology, Inc.

    Inventor： Benjamin Gordon ,  Ohad Michel ,  Matthew Kahlscheuer ,  Benjamin Flores ,  Charles Frazier ,  Louis Perez

    IPC: G06Q30/0601 ,  G06N20/00

    CPC classification number: G06Q30/0627 ,  G06N20/00

    Abstract: The disclosed technology provides for determining infection in food items using image data of the food items under ultra-violet (UV) light. A method includes performing object detection on the image data to identify a bounding box around each of the food items in the image data, determining, for each food item, an infection presence metric by applying a model to the bounding box, the model being trained using image training data of other food items under UV light, the image training data being annotated based on previous identifications of a first portion of the other food items having infection features and a second portion having healthy quality features, and determining, based on a determination that the infection presence metric for each of the food items indicates presence of an infection, an infection coverage metric for the food item.

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