4results about How to "Prevent misidentification" patented technology

This invention proposes a touch display device for use with an active pen. During touch sensing, the touch position is detected. During active pen sensing, an uplink signal is transmitted and a downlink signal is detected. When a downlink signal is detected, it is determined whether the distance between the active pen position and the touch position is less than or equal to a first preset distance; if so, the device does not enter active pen mode.

This invention relates to the field of object recognition technology for nerves, and more particularly to a deep learning-based real-time intraoperative localization and monitoring system for recurrent laryngeal nerve surgery. The system includes a preoperative analysis module to acquire the expected nerve path sequence to determine a first variation risk region; an intraoperative acquisition module to acquire intraoperative video, electromyographic signals, and sequences corresponding to instrument positions; a priori constraint recognition module to determine the intraoperative nerve recognition path sequence and visual recognition confidence level; a path deviation correction module to correct the intraoperative nerve recognition path sequence and visual recognition confidence level; a distance state analysis module to determine whether the real-time distance between the instrument and the nerve is within a distance boundary state; and a warning monitoring module to determine the existence of hidden warning regions based on spontaneous electromyographic activity indicators combined with visual recognition correction confidence level, and to monitor the rate of change of spontaneous electromyographic activity indicators to indicate the nerve stress response state. This invention improves the accuracy of real-time intraoperative localization and monitoring of recurrent laryngeal nerve surgery.

The invention discloses a multi-source remote sensing image enhancement method, device and equipment and a storage medium, and the method comprises the steps: collecting a multi-source remote sensing image, carrying out the preprocessing of the multi-source remote sensing image, and constructing an initial image sample library; performing distortion elimination processing on the first-resolution image in the initial image sample library, and performing correction processing on the second-resolution image to obtain a paired image sample library; constructing a deep learning resolution enhancement network combining a stacked architecture and an attention mechanism; a progressive training strategy is adopted, and the target image sample library is utilized to train the deep learning resolution enhancement network; and inputting a to-be-enhanced remote sensing image into the well-trained deep learning resolution enhancement network to generate an enhanced multi-source remote sensing image. According to the method, through sample library construction, distortion elimination, network design and a training strategy, the generated image gives consideration to high spatial resolution and high temporal resolution at the same time, and the generalization ability and the enhancement effect of the model are enhanced.