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    Ultraviolet light and machine learning-based assessment of food item quality
    1.
    发明授权
    Ultraviolet light and machine learning-based assessment of food item quality 有权

    公开(公告)号：US11847681B2

    公开(公告)日：2023-12-19

    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: G06Q30/00 ,  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.

    ULTRAVIOLET LIGHT AND MACHINE LEARNING-BASED ASSESSMENT OF FOOD ITEM QUALITY
    3.
    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.

    GAS PHASE TREATMENT OF PRODUCE
    5.
    发明公开
    GAS PHASE TREATMENT OF PRODUCE 审中-公开

    公开(公告)号：US20230292776A1

    公开(公告)日：2023-09-21

    申请号：US18124540

    申请日：2023-03-21

    Applicant: Apeel Technology, Inc.

    Inventor： Benjamin Gordon ,  Matthew Kahlscheuer ,  Charles Frazier ,  Jessica Sexton ,  Anthony Crisci

    IPC: A23B7/144

    CPC classification number: A23B7/144

    Abstract: A produce treatment method to mitigate latent infections, such as fungal infections, and to delay ripening in produce is described. The produce treatment method includes providing an antimicrobial agent to an enclosure comprising a plurality of produce items, and contacting the plurality of produce items with the antimicrobial agent, wherein the antimicrobial agent is in gaseous form and is selected to deactivate latent microbes in the plurality of produce items.

    ULTRAVIOLET LIGHT AND MACHINE LEARNING-BASED ASSESSMENT OF FOOD ITEM QUALITY
    6.
    发明公开
    ULTRAVIOLET LIGHT AND MACHINE LEARNING-BASED ASSESSMENT OF FOOD ITEM QUALITY 审中-公开

    公开(公告)号：US20240062265A1

    公开(公告)日：2024-02-22

    申请号：US18499544

    申请日：2023-11-01

    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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