6results about How to "Reduce false recognition rate" patented technology

The application discloses a portrait inspection and identification method based on gait cycle decomposition and multi-phase force analysis, and comprises the following steps: extracting the skeleton key points of a target object in a target object image set in a comparison video and the confidence score of each skeleton key point; extracting the features of the target object in the target object image set according to the skeleton key points of the target object, and obtaining the target object features, wherein the target object features comprise basic features, gait cycle features, gait stage features and gait parameter features; integrating the basic features, the gait cycle features and the gait stage features to obtain comprehensive features; respectively calculating the similarity of the target object features and the comprehensive features in the comparison video to obtain similarity calculation results and overall similarity calculation results; and obtaining the identity identification result of the target object according to the similarity calculation results and the overall similarity calculation results.

This application provides a training method for a fingerprint recognition network, a fingerprint recognition method, an apparatus, and a medium. The training method for the fingerprint recognition network includes: determining fingerprint feature matching maps based on a first initial fingerprint image and a second initial fingerprint image; forming a training sample set from multiple fingerprint feature matching maps; and training an original neural network based on the training sample set to obtain a fingerprint recognition network. The technical solution provided by this application solves the problem of difficulty in distinguishing whether two different fingerprint images belong to the same finger, thus reducing the false acceptance and false recognition rates of fingerprint recognition.

The application relates to a multi-protocol adaptive control method, system, device and medium of an LED dimming power supply, which comprises the following steps: receiving a dimming signal output by an external dimming device, and preprocessing the dimming signal to obtain a target input signal; extracting protocol identification features from the target input signal, and constructing a protocol feature vector; matching the protocol feature vector with a preset protocol template library to generate a candidate protocol set and corresponding initial confidence; dynamically correcting the initial confidence by combining historical recognition results, signal quality indexes and output response consistency to determine a target protocol type; calling corresponding protocol analysis rules and control parameter templates according to the target protocol type to generate target dimming control parameters; and adjusting LED drive output based on the target dimming control parameters. The application has the effect of improving the adaptive identification capability of the LED dimming power supply for various dimming protocols.

The application discloses a carotid artery mis-segmentation processing method and device for robot autonomous scanning, and the method comprises the following steps: calculating an average height; controlling the ultrasonic probe to start moving from the starting point of longitudinal scanning, and acquiring a current ultrasonic image in real time; calculating the height mean value and the height standard deviation of the longitudinal profile of the blood vessel; judging whether the longitudinal profile of the blood vessel is a jugular vein; if yes, calculating the moving distance along the X-axis direction of the tool coordinate system at the next moment and the exertion strength at the next moment; otherwise, taking the preset step length and the preset strength as the moving distance and the exertion strength at the next moment respectively, determining the moving direction at the next moment based on the trend of the longitudinal profile of the blood vessel; controlling the ultrasonic probe to move to the position at the next moment, and re-executing the above process until the ultrasonic probe moves to the end point of the longitudinal scanning. The method effectively reduces the adverse effect of carotid artery mis-segmentation on scanning, and ensures that the carotid artery can be continuously and stably tracked.

The application relates to the field of production safety technology, in particular to a safety production hidden danger auxiliary inspection method and system based on an AI model. The method comprises the following steps: constructing an intelligent agent and multiple monitoring points according to original parameters of a production area; obtaining initial monitoring data according to a first-level monitoring strategy set by the intelligent agent, and setting an auxiliary monitoring strategy according to the initial monitoring data; obtaining a feedback data packet according to the auxiliary monitoring strategy; and the intelligent agent generates a hidden danger diagnosis result according to the feedback data packet. Based on the equipment structure parameters of the multiple monitoring points of the production area, comprehensive monitoring of the production area is realized, a correlation diagnosis model is constructed according to historical hidden danger data analysis, a correlation relationship network of the monitoring points and single-type hidden dangers is generated, multiple verifications of single-type hidden dangers are realized, and the misidentification rate of production hidden dangers is reduced. Linkage monitoring of different types of hidden dangers is realized, the overall identification efficiency of production hidden dangers in the production area is improved, and the safe operation in the production area is ensured.

This invention discloses a real-time intraoperative surgical instrument recognition system and method based on AR devices, belonging to the field of medical device management technology. The system includes: an AR glasses terminal, an edge computing unit, a surgical instrument library, a text matching module, and a highlight rendering module. The AR glasses terminal includes a camera module, a built-in display, and a voice input module, for use by surgical nurses. The edge computing unit receives a video stream and performs frame-by-frame decomposition, identifying instruments in the image using a surgical instrument recognition algorithm. This invention employs a hierarchical recognition algorithm to segment instruments into multiple layers, accurately matching each independent part with the corresponding feature information in the surgical instrument library, and then combining the matching probabilities of each part to determine the final recognition result. This invention effectively solves the problem of distinguishing similar instruments, significantly reduces the recognition error rate, and provides a guarantee for the safe and smooth conduct of surgery.