5results about How to "Reduce data storage" patented technology

The application belongs to the technical field of radar signal processing and imaging, and provides a differential coupling single-frequency time-varying low-quantization imaging method, which comprises receiving a SAR echo signal, constructing a single-frequency time-varying threshold signal, single-bit quantization processing of a reference channel, single-bit quantization processing of a phase shift channel, double-channel data fusion and harmonic cancellation, and imaging processing based on a synthesized signal. The application effectively reduces the quantization noise base and improves the detection capability of a SAR system on weak targets under the premise of not significantly increasing the hardware cost.

The present application relates to the technical field of fabric detection, and particularly relates to a fabric flaw intelligent detection method and system based on machine vision, which comprises the following steps: performing gray-scale processing, geometric correction and denoising, illumination compensation and texture enhancement processing on the fabric image collected under controlled illumination, extracting edges and tracking contour point sequences; calculating outer angles, directionality and signed curvatures based on local point sets, combining concave-convex discrimination, key point reservation, thinning and anti-aliasing smoothing, and reconstructing continuous defect boundary trajectories; and then matching with a defect feature interval library to output defect types and boundary positioning information. Through the present application, the problems of missing detection / mis-detection and unstable positioning of defect boundaries under complex texture and illumination fluctuation conditions in the prior art are solved.

This invention discloses a method and system for epilepsy monitoring and early warning, relating to the field of medical signal processing. It solves the problems of high false alarms and false negatives, and low energy efficiency in existing monitoring technologies due to physiological artifact interference, individual differences, and continuous high power consumption. The key technical points are: first, achieving deep artifact removal of the signal through multi-angle collaborative filtering; second, constructing a personalized lightweight prediction model based on historical data similarity matching and transfer learning; and finally, employing a dynamic signal filtering and graded power adjustment mechanism. This achieves the technical effect of significantly improving the accuracy of early warning for patients with specific lesions while greatly reducing system redundancy and energy consumption.

Embodiments of the present application provide a picture search method, an electronic device, a storage medium and a program product, comprising: in response to receiving a picture search request, obtaining a text semantic feature and a keyword of a search text, the search text being carried in the picture search request; in the case of obtaining the keyword, searching a picture information set respectively matched with the text semantic feature and at least one keyword from a picture information library to obtain a candidate picture information set; and selecting a candidate picture information satisfying a preset condition from the candidate picture information set as a picture search result according to a similarity corresponding to each candidate picture information in the candidate picture information set, the similarity being a similarity between a picture global feature of the corresponding candidate picture information and the text semantic feature. The scheme can improve the picture search efficiency, reduce the calculation overhead, and also take into account the recall rate and accuracy of the picture search, and reduce the index persistence cost of the semantic vector.

The application discloses an MES-based production data management system and method, relates to the technical field of data calculation, and comprises the following steps: obtaining production data of each production manufacturing stage in a manufacturing execution system; calculating data values of the production data based on the outlying characteristics of each production data; when the data values meet preset conditions, screening first storage data which needs full storage and second storage data which needs partial storage from the production data; matching each first storage data and second storage data with a storage server based on the data values and the storage cost of the storage server, determining the corresponding relationship between the production data and the storage server, and storing the production data in each storage server based on the corresponding relationship. The application achieves the technical effects of reducing the difficulty and cost of local maintenance of a super large data table in the later stage.