Ping An Insurance (Group) Company of China has patented a target cell marking method involving deep learning detection to mark cells in images. The method includes converting scanned images, segmenting into blocks, detecting target cells, marking them, and displaying the final image. GlobalData’s report on Ping An Insurance (Group) Company of China 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 Ping An Insurance (Group) Company of China, Digital lending was a key innovation area identified from patents. Ping An Insurance (Group) Company of China's grant share as of February 2024 was 21%. Grant share is based on the ratio of number of grants to total number of patents.
Image-based target cell marking method on terminal device
A recently granted patent (Publication Number: US11929048B2) discloses an image-based target cell marking method that involves obtaining an original scanned image, converting it into a preset image format, segmenting it into multiple image blocks, inputting these blocks into a deep learning detection model to identify target cells, integrating the blocks to mark the target cells, and finally converting the marked image back to its original format for display. The method also includes training the deep learning detection model by selecting sample image blocks, marking standard position information of target cells, adjusting model parameters, and determining errors to ensure accurate detection and marking of target cells.
Furthermore, the patent describes a computer-readable storage medium and a terminal device that implement the image-based target cell marking method. The terminal device includes a memory, a processor, and a computer-readable instruction stored in the memory, enabling the processor to execute the steps of obtaining, converting, segmenting, inputting into the deep learning detection model, integrating, marking, and displaying the image. The method also involves training the deep learning detection model by selecting sample image blocks, marking standard position information and cell types of target cells, adjusting model parameters based on errors, and ensuring the completion of training based on preset conditions. Overall, the patented method and devices aim to efficiently mark target cells in images using deep learning technology, ensuring accuracy and reliability in cell detection and marking processes.
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