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    Ultraviolet light and machine learning-based assessment of food item quality
    2.
    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.

    PRODUCE QUALITY ASSESSMENT AND PRICING METRIC SYSTEM
    8.
    发明申请
    PRODUCE QUALITY ASSESSMENT AND PRICING METRIC SYSTEM 有权

    公开(公告)号：US20220327685A1

    公开(公告)日：2022-10-13

    申请号：US17718447

    申请日：2022-04-12

    Applicant: Apeel Technology, Inc.

    Inventor： James Rogers ,  Jordan Hudson ,  Charles Frazier ,  Taylor Hayward

    IPC: G06T7/00 ,  G06V20/68 ,  G06Q30/02

    Abstract: Systems and methods described herein can non-destructively determine current produce quality. An evaluation system can, at a first time, receive image data of produce and identify a type of the produce using machine learning techniques. The produce can be sent to an end-consumer retail environment. A quality assessment system can, at a second time, receive, from a user device in the retail environment, a request for a current quality of a particular produce that includes scanned data of that produce. The quality assessment system can identify that produce, retrieve, from a data store, machine learning trained models for identifying quality features of that produce, determine, based on applying the models to the scanned data, a current quality of that produce, and transmit, to the user device, the current quality. The produce's price can also be dynamically adjusted based on the current quality of that produce.

    SYSTEM AND METHOD FOR HYPERSPECTRAL IMAGE PROCESSING TO IDENTIFY FOREIGN OBJECT
    10.
    发明申请
    SYSTEM AND METHOD FOR HYPERSPECTRAL IMAGE PROCESSING TO IDENTIFY FOREIGN OBJECT 有权

    公开(公告)号：US20210174495A1

    公开(公告)日：2021-06-10

    申请号：US17125451

    申请日：2020-12-17

    Applicant: Apeel Technology, Inc.

    Inventor： Lars Gustav Magnus Nipe ,  Abilasha Ramanan

    IPC: G06T7/00 ,  G06T7/11 ,  G06K9/62 ,  G06K9/46 ,  G06T19/00 ,  G06K9/42

    Abstract: A system includes a memory and at least one processor to acquire a hyperspectral image of a food object by an imaging device, the hyperspectral image of the food object comprising a three-dimensional set of images of the food object, each image in the set of images representing the food object in a wavelength range of the electromagnetic spectrum, normalize the hyperspectral image of the food object, select a region of interest in the hyperspectral image, the region of interest comprising a subset of at least one image in the set of images, extract spectral features from the region of interest in the hyperspectral image, and compare the spectral features from the region of interest with a plurality of images in a training set to determine particular characteristics of the food object and determine that the hyperspectral image indicates a foreign object.

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