8results about How to "Quick automatic identification" patented technology

The invention relates to the technical field of sensor connection, and discloses a connection method and device for a sensor and an acquisition storage medium and computer equipment, and the method comprises the steps: obtaining a sensor with independent identification information, and configuring a plurality of candidate connection interfaces of the acquisition storage medium to obtain a plurality of connection interfaces with unified attributes; the method comprises the following steps: physically connecting a sensor with any connection interface with unified attributes in an acquisition storage medium to obtain an initial connection state; performing identity recognition by adopting a target recognition technology to obtain recognition information; the sensor information is checked, a data collection scheme is generated, the data collection scheme is used for collecting physical change data of valve operation, and the physical change data is stored through a collection storage medium. The method is applied to the field of valve diagnosis and has a reliable and convenient sensor information management mechanism and a super-convenient sensor use mechanism; and a super-wide standby interface strategy is unified, and more types of sensors can be compatible.

The invention discloses a safety helmet wearing detection method and device in a construction scene and a medium, an image is divided into grids, a sliding window is constructed to extract feature information in the grid image, the calculation amount is reduced, the problem of imbalance between positive and negative samples is relieved, the amplitude of an anchor frame in each direction is obtained through descriptors, and the safety helmet wearing detection accuracy is improved. According to the method, the gradient magnitude in the neighborhood in the interpolation direction is obtained, feature point positioning is performed based on the gradient magnitude, and the anchor frame is screened, so that a target object can be accurately positioned, the detection accuracy is improved, more accurate identification data is obtained by eliminating splicing gaps, and the image is denoised to improve the image quality, so that the image identification precision is improved. According to the invention, the method optimizes the training process of the model, improves the generalization capability and processing speed of the model, can achieve the quick and automatic recognition of whether a worker in a construction site wears a safety helmet or not, improves the safety management efficiency, and reduces the safety accidents caused by not wearing the safety helmet.

The utility model discloses a kind of compressor identification detection structure and breast machine for breast machine.The described compressor identification detection structure includes photoelectric detection module and compressor, the photoelectric detection module is installed in the installation port, the compressor is provided with the lead-in seat compatible with the installation port, the lead-in seat is provided with locking module and detection identification board, the locking module is locked in the installation port when the lead-in seat is inserted into the installation port, the detection identification board is detected by the photoelectric detection module when the lead-in seat is inserted into the installation port;Breast machine includes breast machine host, the breast machine host is provided with riser and bearing table, the bearing table is located below the riser, the riser is provided with installation port, the installation port is provided with the described identification detection structure, and the breast machine host is electrically connected with remote control system. The utility model is applied to the technical field of breast machine.

The invention provides a secondary image deviation measurement system, and relates to the technical field of measurement. The secondary image deviation measuring system comprises a light source which is arranged on the first side of the glass to be measured and is used for emitting light; the image position obtaining device is arranged on the second side, opposite to the first side, of the glass to be detected, the image position obtaining device and the light source are coaxially arranged, and the light source forms a main image and an auxiliary image on the image position obtaining device through the glass to be detected; the image position obtaining device is used for determining the main image coordinates and the auxiliary image coordinates and obtaining an auxiliary image deviation value according to the main image coordinates and the auxiliary image coordinates. Therefore, the secondary image deviation measurement system provided by the invention can realize automatic identification of the secondary image deviation value quickly and accurately, can realize dynamic measurement, and is high in automation degree, convenient to use and high in measurement accuracy.

This invention discloses a method and system for detecting social media rumors based on the BLRQ-BV model, belonging to the technical field of social media content security and information authenticity identification. It includes: encoding each rumor event as a whole into a text modality and a grayscale image modality, constructing a bimodal data representation that maintains semantic integrity; using a BiLSTM network to extract sequence features from the text, employing a specially designed low-discrimination-information-loss quantum hybrid network LIL-QHN to extract quantum features from the text, and using a ResNet-18 network to extract visual structural features from the grayscale image; losslessly fusing the three modal features through an innovative spherical spatial vector synthesis method VC-BS, preserving the feature strength and directional relationships; and introducing a joint loss function to collaboratively optimize each branch, ultimately achieving end-to-end rumor detection. This invention can robustly achieve automatic identification of social media rumors and is applicable to scenarios such as network content security management, public opinion monitoring and early warning, and digital forensics.

This invention relates to the field of sensor connectivity technology, and discloses a method, apparatus, and computer device for connecting a sensor to a data acquisition and storage medium. The method includes: acquiring a sensor with independent identification information and configuring multiple candidate connection interfaces of the data acquisition and storage medium to obtain multiple connection interfaces with unified attributes; physically connecting the sensor to any one of the connection interfaces with unified attributes in the data acquisition and storage medium to obtain an initial connection state; using target recognition technology for identification to obtain identification information; performing sensor information calibration and generating a data acquisition scheme, which is used to acquire physical change data of valve operation and store the physical change data through the data acquisition and storage medium. This invention is applied to the field of valve diagnosis, possessing a reliable and convenient sensor information management mechanism, a highly convenient sensor usage mechanism, a unified and extremely broad backup interface strategy, and compatibility with more types of sensors.

The invention discloses a method and a device for identifying tampering of a software license, a storage medium and a product. The identification method comprises the following steps: segmenting a plurality of sequences from a license text corresponding to a to-be-identified software license; the sequence is used for representing information related to the license range of the software license; text features are extracted from each sequence, and corresponding license feature characters are obtained; wherein the license feature characters are used for representing key characters related to the license range; using the trained recurrent neural network model to identify whether the license feature characters corresponding to the plurality of sequences are tampered or not, and obtaining an identification result of whether the software license is tampered or not; in an iterative training process of the trained neural network model, predicting weight adjustment gradients of parameters corresponding to license feature characters in the recurrent neural network model based on a permutation feature importance method, and adjusting weights of the corresponding parameters based on the weight adjustment gradients of the parameters; and until the newest adjusted recurrent neural network model converges.

The application discloses a kind of based on deep learning multi-beam radio frequency OAM positioning identification method and system, the method and system use optical orbital angular momentum as the basis of pre-training, using pre-training weight information trains radio frequency orbital angular momentum image, and realizes the positioning and identification function of radio frequency orbital angular momentum.The trained deep learning model of the application can automatically identify the real radio frequency orbital angular momentum image received in real time, without manual discrimination, thereby simplifying the operation process of technical personnel.The application reduces the training time, realizes the automation of identification, improves the spectrum utilization, and helps the demultiplexing system of radio frequency OAM system.