3results about How to "Realize intelligent evaluation" patented technology

This application relates to a method, system, device, and medium for intelligent screening of clothing images. The method includes: acquiring a dataset of clothing images to be processed; performing basic quality filtering to obtain a screening set; performing image enhancement on the screened images to generate a standardized set; extracting the visual feature vector and quality score of each image; identifying the main body region based on the features using a clothing region segmentation model to generate a mask; combining the mask and features to extract semantic labels of design elements to form a structured design point set; matching the design point set with a pre-built clothing trend database to generate a trend matching score; simultaneously calculating a design innovation score based on its historical frequency of occurrence; dynamically weighting the quality score, trend score, and innovation score to generate a comprehensive score; and finally, performing a hierarchical decision based on the comprehensive score and quality score, outputting the images to be added to the database and their corresponding level labels. This application realizes intelligent evaluation and screening of clothing designs.

The application relates to the technical field of blasting effect evaluation, and discloses a millisecond blasting effect intelligent evaluation and analysis method, a system and a medium, the method comprises the following steps: arranging a plurality of source sensors to collect vibration, displacement, hydraulic support stress and surface deformation data before and after blasting, and constructing a standardized blasting data set; calculating a vibration amplitude variation based on stress wave propagation characteristics, and determining a crushing effect; combining displacement increment and mine pressure intensity to evaluate rock mass stability and working face safety; forming a response parameter set through multi-time sequence node monitoring, dividing a monitoring partition, comparing predicted and actual indexes, and generating a verification result; feeding back a correction evaluation threshold, and iteratively optimizing blasting effect evaluation. The application can realize accurate, dynamic and closed-loop intelligent evaluation of the millisecond blasting effect.

The application provides a scientific and technological literature innovation evaluation method based on a large model Agent technology, comprising: hierarchical classification of each citation source in a citation dataset in disciplines and research branches, determination of the discipline field code and specific research branch code thereof according to a discipline classification system, and obtaining citation distribution data containing complete classification labels; statistics of the number and proportion of citations of each research branch in the citation distribution data, and calculation of the crossing degree of the literature among different research branches; the large model Agent comprehensively evaluates the innovation value of the literature based on the crossing degree among the branches and the total number of citations, adjusts the weight of different literature according to the crossing degree among the branches, and generates an innovation value score dataset; the large model Agent cross- validates the candidate literature list, confirms the effectiveness of the cross-disciplinary breakthrough characteristics in combination with the information of the proportion of the number of citations of each branch, completes the final labeling, and identifies the breakthrough innovative literature.