Rakuten Group had 63 patents in artificial intelligence during Q2 2024. The Rakuten Group Inc filed patents in Q2 2024 for various systems and methods including image processing, real-time services in O-RAN architecture, population distribution prediction using satellite images, display control based on user characteristics, and object detection and color extraction in images. These patents cover a range of technologies aimed at improving image processing, user experience, and data analysis. GlobalData’s report on Rakuten Group gives a 360-degree view of the company including its patenting strategy. Buy the report here.
Rakuten Group had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Image processing system, image processing method, learning system, and information storage medium (Patent ID: US20240212102A1)
The patent filed by Rakuten Group Inc. describes an image processing system that involves acquiring images with different resolutions, applying color adjustments to specific target pixels, and generating color-adjusted images based on transformation functions and parameter maps. The system utilizes a training model to minimize errors between learning color-adjusted images and correct color-adjusted images. Additionally, the system includes features such as acquiring composite images, using symmetric matrices for transformation, and training the parameter map estimation model with machine learning techniques.
Furthermore, the patent outlines a learning system and method for image processing, as well as a computer-readable storage medium containing a program for implementing the described image processing system. The system involves acquiring training data, calculating color-adjusted pixel value vectors, and generating color-adjusted images based on transformation functions and parameter maps. The training process aims to reduce errors between learning color-adjusted images and correct color-adjusted images, with a focus on increasing similarity and decreasing dissimilarity between images. The system also includes features such as acquiring learning images, masks, and parameter maps, as well as utilizing machine learning models for training and optimization.
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