Contemporary Amperex Technology had 12 patents in artificial intelligence during Q4 2023. The patents filed by Contemporary Amperex Technology Ltd in Q4 2023 involve a defect detection method using grayscale values and mapping tables, as well as a system for generating image samples with specific features using a generative adversarial network. The defect detection method segments images based on grayscale values to identify suspicious defects, while the image sample generation system utilizes semantic segmentation and real images to generate samples with specific features. GlobalData’s report on Contemporary Amperex Technology gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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Contemporary Amperex Technology grant share with artificial intelligence as a theme is 33% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Defect detection method, device and system (Patent ID: US20230419472A1)
The patent filed by Contemporary Amperex Technology Ltd. describes a defect detection method that involves obtaining the average grayscale value of an image, constructing a mapping table based on this value, searching for mapped values corresponding to each pixel's grayscale value, segmenting the image to identify suspicious defect sub-images, and inputting these sub-images into a machine learning model for analysis. The method aims to improve defect detection accuracy by utilizing a combination of grayscale value analysis and machine learning techniques.
The patent also includes detailed claims outlining specific steps and parameters involved in the defect detection method, such as contrast stretching to expand the grayscale value range, using a residual neural network model for analysis, and segmenting the image based on mapped values. Additionally, the patent covers the application of this method to detect defects in objects like electrode plates of batteries, particularly lithium batteries. The apparatus, system, and computer-readable storage medium described in the patent further emphasize the practical implementation and scalability of the defect detection method for various industrial applications.
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