US 11,864,562 B2
Systems and methods for managing meat cut quality
Parul Aggarwal, Bengaluru (IN); Mangesh N. Kulkarni Wadhonkar, Hyderabad (IN); Amit Jhunjhunwala, Bangalore (IN); Rahul Kumar, Bangalore (IN); Raghav Mehta, Bengaluru (IN); and Peeyush Taneja, Delhi (IN)
Assigned to Walmart Apollo, LLC, Bentonville, AR (US)
Filed by Walmart Apollo, LLC, Bentonville, AR (US)
Filed on Oct. 27, 2022, as Appl. No. 17/974,657.
Application 17/974,657 is a continuation of application No. 16/916,682, filed on Jun. 30, 2020, granted, now 11,497,221.
Claims priority of provisional application 62/899,955, filed on Sep. 13, 2019.
Claims priority of application No. 201941029121 (IN), filed on Jul. 19, 2019.
Prior Publication US 2023/0046491 A1, Feb. 16, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. A22C 17/00 (2006.01); G06T 7/00 (2017.01); G06T 7/50 (2017.01); G06F 18/24 (2023.01); G06F 18/40 (2023.01); G06F 18/214 (2023.01); G06V 10/764 (2022.01); G06V 10/80 (2022.01); G06V 10/82 (2022.01); G06V 20/64 (2022.01); G06V 20/68 (2022.01)
CPC A22C 17/008 (2013.01) [G06F 18/214 (2023.01); G06F 18/24 (2023.01); G06F 18/40 (2023.01); G06T 7/001 (2013.01); G06T 7/50 (2017.01); G06V 10/764 (2022.01); G06V 10/803 (2022.01); G06V 10/82 (2022.01); G06V 20/64 (2022.01); G06T 2207/10028 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30128 (2013.01); G06V 20/68 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A system ensuring quality for cuts of meat, the system comprising:
an image capture device, wherein the image capture device is configured to capture an image of a cut of meat;
a depth sensor, wherein the depth sensor is configured to capture depth data associated with the cut of meat;
a database, wherein the database is configured to store meat cut specifications; and
wherein the database, the depth sensor, and the image capture device are each remotely located from each other and are coupled to a control circuit, and wherein the control circuit is configured to during an execution phase subsequent to a training phase:
receive, from the image capture device, the image of the cut of meat and receive from the depth sensor the depth data associated with the cut of meat;
retrieve, from the database, a meat cut specification associated with the cut of meat;
evaluate the cut of meat based on the meat cut specification associated with the cut of meat, and the image of the cut of meat and the depth data associated with the cut of meat; and
classify the cut of meat based on the evaluation of the cut of meat;
wherein the meat cut specification is created by the control circuit using a neural network model during the training phase, wherein during the training phase the control circuit receives training images including markings, wherein the training images with the markings are presented on a screen of an electronic device with a plurality of classification indicators, each of the plurality of classification indicators indicating a meat classification, wherein the markings in the training images are provided onto the image by a user utilizing the electronic device, and wherein the user designates each of the areas in each of the images indicated by the markings as being properly or improperly cut by selecting a classification indicator on the screen to associate with the designated area, wherein during the training phase the control circuit generates, using the neural network model, the meat cut specification based upon an analysis of the areas in the training images bounded by the markings and the designations of the user.