6results about How to "Widely deployed" patented technology

The invention discloses an improved YOLOv11 crack identification and quantification method for a strip mine area and a slope thereof. The method comprises the steps of data preprocessing, model improvement and adaptability adjustment, initial identification model training, crack detection by applying a target identification model, local area identification and post-processing. According to the method, technical means such as a feature extraction network improvement method based on an AReLU function and an ACmix model and a self-adaptive local threshold segmentation algorithm based on a gray scale standard deviation are introduced, and efficient and accurate recognition of cracks is achieved. According to the method, the automation degree of crack detection is improved, the labor cost and the time cost are reduced, and the method is of great significance to safety monitoring of the strip mine area.

The invention discloses a heterogeneous environment prediction model training and deployment method and system, and relates to the field of prediction model training. In order to overcome the defects that an existing model training and deployment method is large in development difficulty, low in deployment efficiency and lack of unified management of multiple versions, an integrated development environment and an integrated development framework are used, and multiple pre-training models and operators are built in; carrying out data preprocessing and exclusive model building, obtaining training data to carry out model training, and generating a training model; all training models are arranged in a model center for unified management; aPI service development is carried out, a unified model algorithm reasoning framework is adopted, self-defined service development is carried out, and self-defined AI service is generated; the AI service is audited and published to be online, and the online AI service is used by an external application; based on distributed task scheduling and service arrangement, AI services are scheduled and run on a service running platform. The method is mainly used for establishing the prediction model for the heterogeneous environment.

A method for counting system terminal devices in a NATed network based on an optical network belongs to the field of data communication. The method utilizes the high-speed transmission capability and low-latency characteristics of the optical network to monitor and count Windows system terminal devices in a home network in real time; the number of terminal devices is counted based on the rate of change of the IP‑ID sequence with the packet arrival time, and different terminal devices are accurately distinguished by analyzing the monotonicity of the IP‑ID field in the DNS request packet and the difference in the growth rate of the IP‑ID sequence between different devices. The present invention can effectively identify the number of terminal devices, enhance the operator's insight into user needs, and thus provide more personalized services and resource allocation solutions. At the same time, the present invention adopts a fixed pattern algorithm, which reduces the consumption of computing resources and speeds up the recognition speed. It is very suitable for the scenario of real-time terminal device number recognition, and further enhances the stability and reliability of the system.

The invention relates to the technical field of damage detection of oil and gas transportation pipelines, in particular to a marine pipeline damage degree intelligent identification method based on multi-source feature deep fusion. The method comprises the following steps: S1, acquiring damage data of a damaged pipeline; s2, performing noise reduction on the damage data by adopting an improved wavelet threshold noise reduction method; s3, performing normalization processing on the data after noise reduction; s4, inputting the normalized data into a preset multi-feature deep fusion white box model for training; and S5, calculating the accuracy to reflect the accuracy of model identification. The method overcomes the defects of a hard threshold function and a soft threshold function, flexibly switches between the hard threshold function and the soft threshold function by adjusting the factor alpha, reduces discreteness, avoids the problem of constancy, is high in adaptability, can be automatically adjusted according to different signal characteristics, effectively removes the noise of experimental acquisition data, improves the signal quality, and greatly improves the identification accuracy of the damage degree.

The application discloses a kind of 5G uplink real-time video transmission oriented time delay compensation control method and system, belong to wireless network real-time video transmission optimization technical field.The application is to solve the problem of time delay inaccuracy and control misjudgment caused by base station scheduling waiting, batch resource release and link layer retransmission in 5G uplink real-time video transmission, by sending end disabling step module to realize video frame burst transmission, and using the flow pattern analysis of receiving end and uplink scheduling estimation to identify scheduling additional influence, construct scheduling additional occupancy ratio to generate correction time delay and feedback to sending end for controller adaptation.The application can estimate and compensate the additional time delay component related to wireless scheduling waiting, batch resource release and potential link layer retransmission, improve the accuracy of sending end in judging real link state, with the advantages of low engineering modification cost, strong commercial adaptability and low computational complexity.

The utility model belongs to self -service equipment technical field discloses a kind of self-service coin changer, including machine body, coin receiving module, coin identification module, coin classification module, paper money exchange module and control module. Coin receiving module is used to receive the coin that user inputs, coin identification module is used to identify denomination and authenticity of coin in real time, coin classification module is used to store the coin after identification according to denomination, paper money exchange module is used to exchange coin into paper money according to user demand, and control module is used to coordinate the work of each module and provide user interactive interface. The utility model realizes the quick, accurate exchange of coin by integrating high-precision identification technology and automatic exchange mechanism, compact structure, easy operation, applicable to bank, shopping mall and other places, significantly improve the efficiency and user experience of coin processing.