10results about How to "Quick and accurate identification" patented technology

This invention discloses a leak detection device equipped with a leak detection block (750), comprising: a main fuel line connection hole (762a) penetrating the center of the body; a first annular spatial connection groove (782) formed at a predetermined depth from one side surface of the body, located radially spaced from the center of the main fuel line connection hole (762a); a second annular spatial connection groove (792) formed at a predetermined depth from the other side surface of the body, located radially spaced from the center of the main fuel line connection hole (762a); and a first separator insertion hole (810) drilled from the outer peripheral surface of the body, spanning the first annular spatial connection groove (782a). 2) The second annular space connecting groove (792) is connected to each other in a communicative manner, wherein when the separator (850) is inserted into the first separator insertion hole (810), the head (852) of the separator (850) closes the portion of the first separator insertion hole (810) between the first annular space connecting groove (782) and the second annular space connecting groove (792), thereby closing the communicative connection between the first annular space connecting groove (782) and the second annular space connecting groove (792), while communicatively connecting the sensor insertion hole (854) leading to the end surface of the head (852) to the first annular space connecting groove (782) or the second annular space connecting groove (792).

The invention belongs to the technical field of contract auditing, and discloses a contract comparison and recognition method based on deep learning, and the method comprises the specific steps: 1, importing a recognition system; step 2, training based on a deep learning OCR model; step 3, performing OCR operation on the picture; 4, identifying and uploading the content; 5, contract output or modification is judged; and step 6, risk prompting. By automatically comparing contract texts, the system can quickly identify key information, the complexity of manual operation is reduced, the system has good adaptability, contracts of different fields and types can be processed without manually adjusting parameters, the manual intervention requirement is greatly reduced due to the high automation degree, contract auditing is more efficient, and the contract auditing efficiency is improved. According to the method, multi-language texts can be easily processed, the automatic data extraction function provides great convenience for subsequent data analysis, and compared with manual text transcription, the OCR technology has better cost benefits in large-scale document processing.

The application provides a kind of intelligent construction site safety monitoring and abnormal behavior detection method, it is related to behavior identification technical field, including: based on video frame data, through target detection algorithm, personnel and cigarette in the construction site multi-modal data are positioned, to output first detection result;Based on the first detection result, video frame data and construction site multi-modal data in the preset time period, utilize 3D CNN to combine attention mechanism, to output second detection result;Based on the second detection result and construction area security level information, by isolated forest and self-encoder algorithm, get comprehensive abnormal score.

This application discloses a data processing method, apparatus, device, storage medium, and program product, applicable to artificial intelligence scenarios. The method includes: acquiring target text detection data; performing character-to-image conversion on the target text detection data to obtain target visual image information corresponding to the target text detection data; performing visual feature extraction processing on the target visual image information to obtain target image hidden features corresponding to the target visual image information; performing text vectorization processing on the target text detection data to obtain target text features corresponding to the target text detection data; and performing semantic fusion processing on the target text features and the target image hidden features to obtain a quality probability parameter corresponding to the target text detection data. Using this application, text quality can be identified quickly and accurately.

This invention provides a pressure recognition method, apparatus, device, and storage medium, belonging to the field of artificial intelligence technology. The method includes: acquiring labeled physiological signal samples and physiological signal samples to be identified from a target user; inputting the labeled and unlabeled physiological signal samples into a Siamese network to obtain a first depth feature corresponding to the labeled physiological signal sample extracted by a first sub-network of the Siamese network and a second depth feature corresponding to the unlabeled physiological signal sample extracted by a second sub-network of the Siamese network; and, based on the difference between the first and second depth features, using a trained pressure recognition model to obtain the pressure intensity recognition result corresponding to the unlabeled physiological signal sample. This invention, by predicting the pressure intensity difference between two physiological signal samples, achieves the identification of unlabeled physiological samples from the same user using only a single labeled physiological signal sample with pressure intensity annotation.

This invention discloses an intelligent electromagnetic compatibility (EMC) detection system and method based on smart sensors, belonging to the field of EMC detection technology. The system includes an input source acquisition module, a predictive analysis module, and an interference identification module. Its key technical points are: acquiring the ambient temperature of the area to be tested and simultaneously obtaining historical calibration data of the active antenna; wherein the historical calibration data includes at least an electromagnetic near-field distribution map and spectral envelope characteristics; based on the historical calibration data, establishing a logistic regression model to predict the drift law of the active antenna with ambient temperature and obtaining the gain change curve; introducing one-dimensional convolutional analysis of electromagnetic signals to identify electromagnetic interference events, using a built-in rule engine to perform judgment analysis on the gain deviation of each batch of measurements, and triggering adjustment strategies through electromagnetic interference events; this aspect achieves intelligent EMC detection, with real-time calibration and correction during the detection process, improving detection accuracy.

The utility model relates to early warning device technical field, specifically is a kind of auxiliary early warning device for thermal power plant centralized control operation, comprising: mounting block;Rotary lever, the rotary lever rotation is connected in mounting block;Panoramic camera, the panoramic camera fixedly connected in the lower end of rotary lever;Driving mechanism, the driving mechanism is set at one side of panoramic camera to realize panoramic camera rotating function, by gear set transmission mechanism, panoramic camera can realize no dead angle rotation scanning, this not only overcomes the problem that traditional fixed camera exists monitoring blind area, also greatly improves monitoring range and real-time, and operating personnel can obtain the comprehensive view of thermal power plant centralized control area through panoramic camera, promptly discovers and handles equipment abnormal condition, to improve overall security.

The invention belongs to the field of aerospace structure strength analysis, and particularly relates to a method for rapidly identifying stress of a whole-aircraft finite element model plate unit of an aircraft. According to the method, plate unit stress identification is carried out on a plurality of finite element model f06 files which are obtained through calculation and contain a plurality of load working conditions, and according to unit numbers, through traversing the f06 files, identification of the stress of the upper surface and the lower surface of the plate unit is rapidly carried out, so that efficient and accurate output of the stress of the plate unit is realized. The method provides technical support for airplane structure strength design, damage analysis and life evaluation, and can be widely applied to aerospace structure strength analysis.

The present application belongs to the technical field of molecular biology, and particularly relates to a SNP molecular marker combination for identifying or distinguishing grouper germplasm resources and application thereof. Genomic DNA of golden money grouper, tiger grouper and golden tiger hybrid grouper is extracted, and 177 common SNP sites are obtained after detection, and specific position information is shown in Table 1 of the specification. The SNP molecular marker combination screened by the present application can be developed into primers, probes or gene chips, and through simple phylogenetic tree analysis, golden money grouper, tiger grouper and golden tiger hybrid grouper can be quickly and accurately distinguished, and unknown detection samples can also be subjected to genetic phylogenetic tree analysis with known golden money grouper, tiger grouper and golden tiger hybrid grouper, so that it can be quickly and accurately identified which kind of grouper the unknown detection sample belongs to, and the present application has the characteristics of simple operation, high efficiency, high accuracy and the like, and has important significance in grouper germplasm resource protection and utilization and grouper genetic breeding work.

This invention belongs to the field of additive manufacturing technology, specifically an intelligent 3D printing system, including a frame and a controller. The frame houses a laser print head and a powder bed mechanism. The powder bed mechanism lays the powder, which is then melted by the laser print head to complete the cladding process. This intelligent 3D printing system, on the one hand, fully utilizes forward mapping to output results from a trained network in seconds or even milliseconds, greatly accelerating the real-time simulation effect of design iteration. Simultaneously, it can replace time-consuming finite element calculations with neural networks in optimization processes such as genetic algorithms, quickly finding optimal design parameters and effectively achieving optimized design results. On the other hand, it utilizes backward mapping to quickly and accurately identify complex material model parameters, several times faster than traditional trial-and-error methods, and can infer the system's input or physical characteristics based on the structure's dynamic response.