18158925. SYSTEMS AND METHODS FOR PROCESSING IMAGES CAPTURED AT A PRODUCT STORAGE FACILITY simplified abstract (Walmart Apollo, LLC)

SYSTEMS AND METHODS FOR PROCESSING IMAGES CAPTURED AT A PRODUCT STORAGE FACILITY

Organization Name

Walmart Apollo, LLC

Inventor(s)

Raghava Balusu of Achanta (IN)

Avinash M. Jade of Bangalore (IN)

Lingfeng Zhang of Dallas TX (US)

William C. Robinson, Jr. of Centerton AR (US)

Benjamin R. Ellison of San Francisco CA (US)

Srinivas Muktevi of Bengaluru (IN)

Amit Jhunjhunwala of Bangalore (IN)

Zhaoliang Duan of Frisco TX (US)

Siddhartha Chakraborty of Kolkata (IN)

Ashlin Ghosh of Ernakulam (IN)

Mingquan Yuan of Flower Mound TX (US)

SYSTEMS AND METHODS FOR PROCESSING IMAGES CAPTURED AT A PRODUCT STORAGE FACILITY - A simplified explanation of the abstract

This abstract first appeared for US patent application 18158925 titled 'SYSTEMS AND METHODS FOR PROCESSING IMAGES CAPTURED AT A PRODUCT STORAGE FACILITY

Simplified Explanation: The patent application describes a system for processing captured images of objects using a trained machine learning model and a control circuit.

Key Features and Innovation:

• Utilizes a trained machine learning model to process unprocessed captured images.
• Control circuit associates processed images into different groups based on rules.
• Removes processed images from one group according to a processing rule.
• Outputs remaining processed images for retraining the machine learning model.

Potential Applications: This technology can be applied in product storage facilities, warehouses, and logistics centers for efficient image processing and object categorization.

Problems Solved: This technology addresses the challenges of automating image processing tasks in storage facilities, improving efficiency and accuracy in object recognition and categorization.

Benefits:

• Increased efficiency in processing captured images of objects.
• Enhanced accuracy in categorizing objects.
• Automation of tasks in product storage facilities.

Commercial Applications: The technology can be used in automated inventory management systems, quality control processes, and security systems in various industries such as retail, manufacturing, and logistics.

Questions about the Technology: 1. How does the trained machine learning model improve the processing of captured images? 2. What are the potential limitations of using this technology in real-world applications?

Frequently Updated Research: Stay updated on advancements in machine learning algorithms for image processing and object recognition to enhance the performance of this technology.

Original Abstract Submitted

In some embodiments, apparatuses and methods are provided herein useful to processing captured images of objects at a product storage facility. In some embodiments, there is provided a system for processing captured images of objects including a trained machine learning model and a control circuit. In some embodiments, the trained machine learning model is configured to process unprocessed captured images. In some embodiments, the control circuit is configured to associate each of the processed images into one of a first group, a second group, or a third group; remove at least one processed image associated with the first group from the processed images in accordance with a first processing rule; and output remaining processed images associated with the first group and processed images associated with the second group to be used to retrain the trained machine learning model.