Zuora. has filed a patent for unsupervised data drift detection for classification neural networks. The method involves comparing artifacts of images and class wise probabilities at different times to detect changes and generate informative communications. GlobalData’s report on Zuora 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 Zuora, Social media analytics was a key innovation area identified from patents. Zuora's grant share as of January 2024 was 54%. Grant share is based on the ratio of number of grants to total number of patents.
Unsupervised data drift detection for classification neural networks
A recently filed patent (Publication Number: US20240037923A1) describes a method for detecting unsupervised data drift using a neural network. The method involves sensing a data stream of images, providing it to the neural network, generating class-wise probabilities, storing images and probabilities in databases, and comparing artifacts at different times. An informative communication is then generated based on these comparisons, indicating when the neural network may not be operating correctly. The method also includes adaptively adjusting weights for the comparisons based on specific values, ensuring accurate detection of data drift.
Furthermore, the patent also describes a system for detecting unsupervised data drift, comprising an image sensor and a processor. The processor receives the data stream, provides it to a neural network, stores images and probabilities, and compares artifacts at different times. An informative communication is generated based on these comparisons, with the system also capable of providing data to retired neural network models for further comparison. This system allows for efficient detection of data drift and alerts system operators when updates to the neural network models are necessary, ensuring optimal performance and accuracy in 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.
