Walmart Apollo, LLC

Qian Li

Alessandro Magnani

Abon Chaudhuri

Theban Stanley

Abilash Amarthaluri

Venkatesh Kandaswamy

Shreyansh Prakash Gandhi

Behzad Ahmadi

Omer Ovenc

Samrat Kokkula

Poornima Candoth

Chhavi Yadav

Ashley Kim

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving one or more digital images; identifying a foreground of the one or more digital images; analyzing the foreground of the one or more digital images to identify a skin region in the foreground of the one or more digital images; when the skin region is identified, clustering a non-skin remainder of the foreground of the one or more digital images into one or more clusters; extracting one or more patches of the one or more digital images from the one or more clusters of the foreground of the one or more digital images; determining one or more scores for the one or more patches of the one or more digital images; and coordinating displaying a patch of the one or more patches on an electronic display based on the one or more scores for the one or more patches. Other embodiments are disclosed herein.

Systems and methods for extracting patches from digital images

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform receiving item data for items from a catalog, assigning a task for evaluation of the item data, storing a plurality of task jobs to a task queue, repeatedly setting, in real time, a respective processor to perform a respective evaluation model, processing the plurality of task jobs stored to the task queue by determining, in real time, whether a first evaluation model set to be performed on a first processor is capable of meeting the first evaluation criteria of the first task data, performing, on the first processor, the first evaluation model on the first task data, and transmitting first first-evaluation-model-output instructions, and repeatedly updating, in real time, the task queue. Other embodiments are disclosed herein.

Systems and methods for processing of catalog items with a plurality of models

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving a digital image comprising multiple items; determining an embedding for the digital image using a machine learning algorithm trained on one or more combined digital images, the combined digital image comprising one or more annotated digital images; identifying an item of the multiple items in the digital image; and facilitating an alteration of a GUI on an electronic device in response to identifying the item in the digital image.

Systems and methods for identifying items in a digital image

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving one or more digital images from a repository of digital images; annotating the one or more digital images from the repository of digital images; digitally altering the one or more digital images, as annotated, from the repository of digital images; digitally combining the one or more digital images, as annotated and digitally altered, with at least one or more portions of one or more other digital images of the repository of digital images to create one or more combined digital images; training a machine learning algorithm on the one or more combined digital images; and storing the machine learning algorithm, as trained, in the one or more non-transitory computer readable storage devices.

Growing community of inventors

Sunnyvale, CA, United States of America

Qian Li