Sharp had 37 patents in artificial intelligence during Q2 2024. Sharp Corp’s patents in Q2 2024 focus on devices configured to perform filtering and frame rate up sampling based on neural network post-filter characteristics messages. These devices can determine neural network updates and provide related information based on extracted information from image data. The patents also involve controlling image processing devices to execute various image processing tasks. GlobalData’s report on Sharp gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Sharp had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Systems and methods for signaling neural network post-filter purpose information in video coding (Patent ID: US20240205462A1)
The patent filed by Sharp Corp. describes a method and device for performing filtering based on information included in a neural network post-filter characteristics message. The method involves receiving the message, parsing syntax elements indicating the purpose of a post-processing filter, and determining whether syntax elements related to input formatting, output formatting, and complexity of the filter are present. The device includes processors configured to perform these parsing functions, with additional capabilities such as specifying the bit depth of chroma sample values and providing updates to previous messages.
The device's processors are further configured to signal the neural network post-filter characteristics message, indicating the purpose of the post-processing filter and specifying the presence of related syntax elements. The device can be used in video decoding and encoding applications, enhancing the efficiency and effectiveness of neural network filtering for video data. The patent highlights the importance of organizing and interpreting information within the neural network post-filter characteristics message to optimize post-processing filter performance.
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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.
