Yamaha Motor had eight patents in artificial intelligence during Q2 2024. The patent filed by Yamaha Motor Co Ltd in Q2 2024 describes a method for generating a learning model used in machine learning to automatically determine the number of target objects in a container. This method involves inputting model data representing the container and target object shapes, creating unit formative assemblies with target objects arranged in a specific array, and generating training image data by applying real textures to the shape image data. GlobalData’s report on Yamaha Motor gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Yamaha Motor had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Method and program for generating trained model for inspecting number of objects (Patent ID: US20240153253A1)
The patent filed by Yamaha Motor Co Ltd describes a method for generating a learning model for machine learning to automatically determine the number of target objects in a container. The method involves inputting model data representing the container and target object shapes, creating unit formative assemblies with target objects arranged in a specific array, generating shape image data of the container with target objects at a specific density, and creating training image data by applying real textures to the shape image data. The process includes simulating the arrangement of target objects in confined areas, freefalling them into the container area, and comparing training image data with actual images to update the learning model.
Furthermore, the method involves setting mixture areas for unit formative assemblies, inducing freefall of unit assemblies into the container area, defining true data for target object positions, storing training image data and true data, and executing physically based rendering for texture processing. The program associated with the method causes a learning model generation device to receive model data, create unit formative assemblies, generate shape image data of the container with target objects, and create training image data with real textures. This innovative approach allows for accurate and automated examination of the number of objects in a container, enhancing efficiency and precision in various applications.
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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.
