RTX had 48 patents in artificial intelligence during Q4 2023. RTX Corp’s patents in Q4 2023 focus on machine learning automatic target recognition decision explanation, network intrusion detection based on network flow data and network sessions, monitoring cargo loading for damage detection, and grouping constituent flows of multiplexed or tunneled flows. These inventions aim to improve security, efficiency, and automation in various industries. GlobalData’s report on RTX gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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RTX grant share with artificial intelligence as a theme is 41% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Object classification based on spatially discriminated parts (Patent ID: US20230419640A1)
The patent filed by RTX Corp. pertains to devices, systems, and methods for machine learning automatic target recognition (ATR) decision explanation. The method involves receiving an object specification matrix from an object model database, receiving feature data indicating the likelihood of features present in an image, determining the probability that the image corresponds to the object based on the object specification matrix and feature data, and providing this probability to aid in classifying the object. The claims detail various aspects of the method, including the object specification matrix indicating feature presence, absence, or movement, generating a new object specification matrix for unknown objects, providing explainability and consistency metrics, using ensemble classifiers for feature data generation, and incorporating uncertainty associated with feature likelihood in determining the probability of object classification.
Furthermore, the method involves estimating the overall size of the object, modifying the probability based on a time series of images and frame weights, considering uncertainty in feature likelihood for image series classification, and updating probabilities in real-time based on user input. The patent also covers a non-transitory machine-readable medium with instructions for ATR decision explanation operations and a device with processing circuitry to execute these instructions. Overall, the patent aims to enhance machine learning ATR decision explanation by providing a systematic approach to analyzing feature data, object specifications, and uncertainties to improve object classification accuracy and user understanding.
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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.
