MediaTek had four patents in edge computing during Q2 2024. MediaTek Inc filed patents in Q2 2024 for enhancing kernel reparameterization of non-linear machine learning models and for XR enhancement in mobile communications. The first patent involves expanding a kernel with a non-linear network, training the model, reparameterizing the network back to a kernel, and deploying the model to an edge device. The second patent focuses on establishing communication with a network node, offloading XR-related computation to enhance XR at the user end in mobile communications. GlobalData’s report on MediaTek gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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MediaTek had no grants in edge computing as a theme in Q2 2024.
Recent Patents
Application: Training framework method with non-linear enhanced kernel reparameterization (Patent ID: US20240160928A1)
The patent filed by MediaTek Inc. describes a method for enhancing kernel reparameterization of a non-linear machine learning model. This method involves expanding a predefined machine learning model's kernel with a non-linear network for convolution operation, training the resulting non-linear model, reparameterizing the non-linear network back to a kernel, and deploying the reparameterized model to an edge device, such as a mobile device. The non-linear network may include various components like non-linear activation layers, squeeze and excitation network, self-attention network, channel attention network, split attention network, and feed-forward network.
The reparameterized machine learning model can be deployed for tasks such as classification, object detection, segmentation, and image restoration, including super resolution and noise reduction. The method specifies the use of a Q×Q kernel for expanding the predefined machine learning model with the non-linear network, where Q is a positive integer. Additionally, the patent also covers a non-transitory computer-readable storage medium containing instructions to implement the method for enhancing kernel reparameterization, further detailing the components of the non-linear network and the deployment scenarios for the reparameterized model on edge devices like mobile devices.
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