6results about How to "Solve extraction difficulties" patented technology

The invention discloses a portable meat doping identification chip and a detection method, and the method comprises the following steps: placing a meat sample slice on a sample bearing layer of the chip, starting the chip to collect a terahertz time-domain spectral signal, and calculating optical parameters of a meat sample in a frequency band of 0.2-2.0 THz; performing principal component analysis on the high-dimensional data of the optical parameters in the whole frequency band to obtain feature vectors; and inputting the feature vector into a pre-trained artificial intelligence model, respectively performing qualitative identification of meat species and quantitative prediction of the doping content, and outputting an analysis report containing a species identification result and a doping ratio.

The application discloses an expert warehousing method and system for petrochemical engineering. The experts to be warehoused are composed of application warehousing experts and designated warehousing experts with high-level professional technology. The method comprises the following steps: collecting basic information and work experience information of historical warehousing experts, analyzing the influence of the operation characteristics of the units to which the experts belong on the experience and professional skills of the experts, and determining multiple expert information classification items as expert extraction conditions; determining whether each application warehousing expert has the qualification of bid evaluation according to the sub-information under each classification item in the reported expert information of each application warehousing expert, then warehousing the experts with the qualification of bid evaluation and the sub-information under each classification item as the warehousing objects to form an initial expert warehouse; and updating the current initial expert warehouse by using the sub-information under the specific classification items configured for each designated warehousing expert, so as to complete the warehousing of experts. The application realizes the warehousing and classification of petrochemical engineering experts.

This utility model discloses a stopper structure for a container, including a container body with an opening at the top. A stopper is detachably mounted on the opening. The stopper includes a stopper body and a insert. The stopper body can be inserted into the opening to seal it. The stopper body has an insertion hole into which the insert can be inserted. Fixed rods are mounted on both sides of the insert, and rotating rods are hinged to the fixed rods. The rotating rod includes a rod body that extends from the inner wall of the insert through the outer wall of the insert. A spring abuts between the two rod bodies. A baffle is fixedly mounted at the bottom of the rotating rod, with the baffle and rod body located on opposite sides of the rotating rod. The baffle can extend under the stopper body and move radially along the stopper body so that it moves upward to abut against the bottom surface of the stopper body. This utility model provides a stopper structure for a container that improves sealing performance while facilitating stopper removal.

The application provides a kind of cross-condition rolling bearing fault targeting migration diagnosis method and system, solve the problem that traditional rolling bearing fault diagnosis algorithm is difficult to extract network deep feature information in source domain and target domain, cannot realize effective cross-domain fault diagnosis.This application uses feature encoder to accurately extract high-dimensional mapping features of the signal from the input rolling bearing vibration signal;Further input the feature to the graph construction layer, mine the deep features of the data, and model the instance graph using the multi-channel kernel graph convolution network;Use the training based on difference and confrontation to minimize the distance between the source domain and target domain distribution, and the classifier uses the extracted domain invariant feature to complete cross-domain fault recognition.Compared with other methods, under the cross-condition of rolling bearing, the deep features can be better extracted for cross-domain transmission, greatly improving the diagnosis accuracy.

This invention relates to a method, apparatus, electronic device, and storage medium for generating road backgrounds. The method includes: acquiring a keyframe image sequence by extracting frames from a source video of an intersection; performing interactive prompt segmentation on the first frame image in the keyframe image sequence to obtain a segmentation mask of the road region in the first frame image and corresponding prompt information; based on the prompt information, segmenting each frame image in the keyframe image sequence except for the first frame image to obtain a segmentation mask of the road region in each frame image; and determining a target image containing only the road region and free of dynamic occlusions based on the segmentation masks corresponding to all frame images. This solution effectively solves the problem of road background extraction in complex scenes by using interactive prompt segmentation and temporal fusion technology, improving the accuracy and stability of background extraction, and providing high-quality background images for applications in fields such as intelligent transportation.

This invention discloses an image recognition method for reinforcing bars, belonging to the field of image recognition technology. The method involves acquiring an image of reinforcing bars with parameter annotations, identifying the parameter annotations within the image, and expanding the range of the parameter annotations based on the pixel density surrounding them. Next, by identifying the contour of the reinforcing bars in the image, and based on the overlap between the contour and the expanded parameter annotations, a main contour containing both the reinforcing bar contour and the parameter annotations is obtained. The main contour is then expanded to retrieve other parameter annotations, resulting in candidate influence regions. Based on the overlap between the main contour and the candidate influence regions, other parameter annotations falling within the candidate response regions are matched with the reinforcing bar contour. This invention establishes a mapping between geometric topology analysis and semantic text extraction, enabling image analysis to possess geometric cognitive capabilities, thereby automatically recognizing the shape and parameter information of reinforcing bars and outputting structured data.