Corning had four patents in artificial intelligence during Q4 2023. The patent filed by Corning Inc in Q4 2023 describes a method and system for inspecting a honeycomb body using image capture, feature detection, graphical representation, and machine learning analysis to classify the structural characteristic of the honeycomb body. GlobalData’s report on Corning gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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Corning grant share with artificial intelligence as a theme is 25% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Structural characteristic prediction for a honeycomb body using image abstraction (Patent ID: US20230334651A1)
The patent filed by Corning Inc. describes a method and system for inspecting a honeycomb body using image processing and machine learning algorithms. The method involves capturing an image of the honeycomb body, detecting specific features related to its structural characteristics, abstracting these features into graphical representations, generating a second image with these representations, and analyzing it using a machine learning algorithm to classify the honeycomb body based on its structural characteristics. The system includes a camera, a controller with a machine learning algorithm, and processes for detecting, abstracting, generating, and analyzing images to classify the honeycomb body.
The method further includes steps such as reducing image resolution, characterizing detected features, using machine vision software for data collection, and determining pass or fail inspection results based on predicted values. Additionally, the patent covers aspects like controlling extruder components during honeycomb body manufacturing based on inspection results, using deep neural networks like convolutional neural networks, and classifying structural characteristics such as isostatic strength or accuracy with respect to a target shape. The imaging system described in the patent involves a camera, a controller with a machine learning algorithm, and processes for detecting, abstracting, generating, and analyzing images to classify the honeycomb body based on its structural characteristics, with features like varying image resolutions and characterizing detected features included in the system design.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
