Hon Hai Precision Industry had 33 patents in artificial intelligence during Q1 2024. Hon Hai Precision Industry Co Ltd has filed patents for machine learning methods for image segmentation, depth recognition models, and reducing depth estimation errors. These methods involve generating feature vectors, matrices, and functions to adjust models for improved accuracy. Additionally, the patents include systems with networked devices equipped with various sensors for identifying target locations or devices based on audio signals. The company also filed patents for image depth prediction methods using monocular cameras to reconstruct frames and improve depth estimation accuracy for dynamic scenes. GlobalData’s report on Hon Hai Precision Industry gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Hon Hai Precision Industry grant share with artificial intelligence as a theme is 15% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Machine learning method (Patent ID: US20240095930A1)
The patent filed by Hon Hai Precision Industry Co Ltd describes a machine learning method that involves distinguishing foregrounds and backgrounds in images, cropping images and mask images, generating feature vectors and matrices, and adjusting models based on functions derived from these matrices. The method includes various steps such as cropping images and masks, calculating foreground rates, and generating matrices based on pixel logic values. Additionally, the method involves resizing masks, extracting features, and adjusting models based on similarity values and positions in the matrices.
Furthermore, the patent outlines a method for generating mask images based on portions corresponding to foregrounds and backgrounds of the original image, determining pixel logic values, and training models using functions derived from these mask images. The method includes cropping images, processing them through a model to generate matrices, and performing calculations based on logic values to create matrices for adjusting the model. It also involves generating matrices based on logic values and similarity values, where changes in these values impact the function used for training the model.
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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.
