ADOBE had 274 patents in artificial intelligence during Q2 2024. Adobe Inc’s patents in Q2 2024 focus on various techniques such as text identification in layered digital content, estimating effects with latent representations, camera pose estimation using deep learning, predicting user intent for image masking based on gestures, and digital content stylization using a neural photofinisher. These techniques leverage machine learning models to enhance digital content creation and manipulation processes. GlobalData’s report on ADOBE gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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ADOBE had no grants in artificial intelligence as a theme in Q2 2024.
Recent Patents
Application: Text identification in layered digital content (Patent ID: US20240212367A1)
The patent filed by Adobe Inc. describes techniques for text identification in layered digital content. The method involves receiving digital content with multiple layers, identifying a text layer within the content, generating a text channel image by isolating the text layer, and creating a text identification using a page decomposition model trained with machine learning. The text channel image may involve converting non-black text to black text and maintaining the text layout from the original content.
Additionally, the system described in the patent includes a processing device and memory component to perform operations such as identifying text layers, generating text channel images, and combining text identifications for display. The page decomposition model utilizes a deep neural network to classify text regions within the text channel image. The patent also covers a non-transitory computer-readable medium storing executable instructions for receiving digital content, separating text channels from additional channels, generating text channel images, and producing text identifications using the page decomposition model trained with machine learning. The text identification may be combined with page text identifications based on the text and additional channels.
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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.
