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    SYSTEM USING MACHINE LEARNING MODEL TO DETERMINE FOOD ITEM RIPENESS
    74.
    发明申请
    SYSTEM USING MACHINE LEARNING MODEL TO DETERMINE FOOD ITEM RIPENESS 有权

    公开(公告)号：US20220299493A1

    公开(公告)日：2022-09-22

    申请号：US17696197

    申请日：2022-03-16

    Applicant: Apeel Technology, Inc.

    Inventor： Richard Pattison ,  Matthew Kahlscheuer

    IPC: G01N33/02 ,  G01N21/3563 ,  G01N21/359 ,  G06N20/00

    Abstract: Systems and methods are disclosed for determining a ripeness, firmness, or consumption suitability for food items, such as produce and fruit. The disclosure can provide for generating a machine learning model to detect food item ripeness. The model can be generated using destructive and non-destructive measurements of one or more food items. The model can then be applied to spectral imaging data of food items in real-time. The spectral imaging data can be captured by a point spectrometer. Using the model and spectral imaging data, the ripeness of the food items can be determined in a non-destructive manner. The determined ripeness of the food items can then be used to determine one or more supply chain modifications.

    OBJECT THROUGHPUT USING TRAINED MACHINE LEARNING MODELS
    75.
    发明申请
    OBJECT THROUGHPUT USING TRAINED MACHINE LEARNING MODELS 有权

    公开(公告)号：US20220270269A1

    公开(公告)日：2022-08-25

    申请号：US17678867

    申请日：2022-02-23

    Applicant: Apeel Technology, Inc.

    Inventor： Richard Pattison ,  Pooyan Abouzar ,  Ohad Michel ,  Tim Rappold ,  Sahana Venkatesh ,  Saurabh Chatterjee

    IPC: G06T7/246 ,  G06T7/292 ,  G06V10/764 ,  G06V10/82 ,  G06T7/60 ,  G06V10/774 ,  G06V20/68 ,  G05B19/4155

    Abstract: Disclosed are techniques for determining object throughput. A method may include obtaining first data representing a first image corresponding to a first time, identifying a first portion of the first data that depicts a first object at a first location, obtaining second data representing a second image corresponding to a second time, identifying a second portion of the second data that depicts the first object at a second location, obtaining third data indicating a counting threshold, determining based at least on the third data and the second location, that the first object satisfies the counting threshold, generating a value indicating a number of objects satisfying the counting threshold, the number of objects including the first object, generating a data value indicating a throughput of the number of objects based on the value indicating the number of objects satisfying the counting threshold and elapsed time between the first and second times.

    PREDICTION OF INFECTION IN PLANT PRODUCTS
    78.
    发明申请
    PREDICTION OF INFECTION IN PLANT PRODUCTS 有权

    公开(公告)号：US20220028496A1

    公开(公告)日：2022-01-27

    申请号：US17499068

    申请日：2021-10-12

    Applicant: Apeel Technology, Inc.

    Inventor： Cody Vild ,  Savannah Braden ,  Matthew Kahlscheuer ,  Louis Perez

    IPC: G16B40/00 ,  A01G22/00 ,  G06N20/00 ,  A01N1/00 ,  A01N3/00 ,  C12Q1/6895 ,  G06N5/04 ,  G06Q10/08

    Abstract: A method for predicting a likelihood of infection in a set of similarly sourced plant products is disclosed. A subset of plant products is selected from the set of plant products. For each plant product in the subset, a level of expression of one or more infection biomarkers, and optionally a level of expression of one more housekeeping biomarkers, are determined. A set of biomarker expression statistics for the subset of plant products is determined based on the determined levels of expression of the one or more infection biomarkers and optionally the levels of expression of the one or more housekeeping biomarkers for each plant product in the subset. A likelihood of infection in the set of plant products is then predicted based at least in part on the determined set of biomarker expression statistics for the subset of plant products.

    System and method for hyperspectral image processing to identify object
    80.
    发明授权
    System and method for hyperspectral image processing to identify object 有权

    公开(公告)号：US10902577B2

    公开(公告)日：2021-01-26

    申请号：US15977085

    申请日：2018-05-11

    Applicant: Apeel Technology, Inc.

    Inventor： Lars Gustav Magnus Nipe ,  Abilasha Ramanan

    IPC: G06K9/00 ,  G06T7/00 ,  G01N33/02 ,  G06T7/11 ,  G06K9/62 ,  G06K9/42 ,  G06K9/46

    Abstract: A system includes a memory and at least one processor to acquire a hyperspectral image of an object by an imaging device, the hyperspectral image of the object comprising a three-dimensional set of images of the object, each image in the set of images representing the object in a wavelength range of the electromagnetic spectrum, normalize the hyperspectral image of the object, select a region of interest in the hyperspectral image, the region of interest comprising 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 object.

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