3 results about "Objective quality" patented technology

The invention relates to a historical case similarity-based quality evaluation method, which belongs to the field of software development, and comprises the following steps of: screening out a prior index and a posterior index; collecting data of each stage in the research and development process of each software historical version as historical cases; the specific numerical value of each index is counted; obtaining quality problem source data of the historical cases; taking the historical cases with the labels as input samples, performing model training by adopting an SVM classification algorithm, and constructing a quality problem classification model; constructing a prior index vector matrix for each historical case and the newly-added case, and calculating the similarity between the newly-added case and each historical case; automatically classifying the newly added cases and setting labels; calculating a risk value of each similar case; and averaging the risk values of all the similar cases to obtain a risk coefficient value of the newly added case. According to the method, the influence of manual subjective deviation on index interpretation can be avoided, and an objective quality evaluation standard is established through quantitative similarity analysis.

This invention relates to the field of text classification technology, and more particularly to a text classification method, medium, and device. It dynamically determines the first parallel inference quantity M using computational resources, achieving a balance between computational resource utilization and inference stability. By initiating multi-threaded parallel inference, it generates M candidate output sequences containing a first intermediate semantic representation and a first text classification result, covering different inference logics of the model for the target text. This approach balances result diversity and inference efficiency, reducing classification errors caused by single-sequence inference bias. Through compliance verification and confidence assessment, it calculates a first quality score to obtain the target classification result. This not only filters sequences containing security risks or structural defects, ensuring the security of the classification process, but also distinguishes the reliability differences of the classification results, avoiding one-sided judgments that ignore reliability based solely on labels. In scenarios without real labels, it achieves objective quality quantification, ensuring the accuracy of the text classification results.

This invention discloses a segmentation system and batch processing and quality assessment method for concrete CT images, aiming to solve the problems of low segmentation accuracy, poor batch processing efficiency, and lack of objective quality assessment for multiphase components in complex gray-scale overlapping scenes. The method includes: preprocessing using adaptive filtering based on local gradient statistics; constructing a multi-scale feature pyramid network containing encoder-decoder and skip connections to generate initial segmentation; introducing a channel-spatial dual attention mechanism to optimize microcracks and pore boundaries; achieving parallel task allocation under heterogeneous computing resources through a batch processing scheduling engine; establishing a multi-dimensional quality assessment system covering segmentation consistency, topological integrity, and structural fidelity, and feeding the assessment results back to the preprocessing and model parameter adjustment units to form a closed-loop optimization. This enables high-precision, high-efficiency, and fully automated intelligent segmentation and quality control of concrete CT images.