AeroVironment. has been granted a patent for a system that processes unstructured image data using multiple machine learning models to generate composite images with object identifiers. The system outputs a video stream of these composite images in chronological order, enhancing object recognition capabilities. GlobalData’s report on AeroVironment gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on AeroVironment, Precision imaging drones was a key innovation area identified from patents. AeroVironment's grant share as of July 2024 was 51%. Grant share is based on the ratio of number of grants to total number of patents.
Composite image generation using multiple machine learning models
The patent US12067768B2 describes a sophisticated system and method for generating composite images using multiple machine learning models to identify various object types within a set of images. The system comprises one or more processors and a non-transitory computer-readable storage medium that contains instructions for processing images received from a recording device. The process involves determining the object types to be recognized, selecting appropriate machine learning models for each object type, and inputting images into these models. The output from each model provides indicators of identified objects, which are then used to create composite images. These images are compiled into a video stream that is displayed in chronological order, enhancing the visual representation of the detected objects.
Additionally, the patent outlines operations for capturing images using unmanned vehicles and transmitting the resulting video stream to a controller. The method includes overlaying indicators on the images to denote detected objects, ensuring that each machine learning model processes distinct object types. The system also incorporates resource management features, allowing for monitoring and adjusting the input to machine learning models based on their resource utilization. This ensures efficient processing while maintaining the integrity of the object recognition tasks. Overall, the patent presents a comprehensive approach to image processing and object recognition, leveraging advanced machine learning techniques to enhance visual data analysis.
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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.
