Rapid identification method based on lightweight DAB-Net network

Abstract

The invention belongs to the field of target identification, and particularly relates to a rapid identification method based on a lightweight DAB-Net network. The method includes: taking a lightweightDAB-Net network structure as a basis, carrying out model quantification; parallelizing the algorithm by adopting multi-thread pipelined calculation; decomposing the algorithm into a plurality of tasks, allocating corresponding pairs of threads, and executing an independent task by each thread; gPU forward propagation operation time is taken as the minimum cycle period, and image reading, data input processing, data output processing and Opencv subsequent processing are included in GPU operation time consumption; awakening other waiting threads through a thread synchronization signal to achieve thread synchronization; data input at the current moment comes from data output of the previous moment and the previous state, and parallel algorithm optimization acceleration is achieved by delaying data output of four frames. According to the invention, the identification speed is improved based on the lightweight DAB-Net network.

Description

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AI Technical Summary

Benefits of technology

This patented system improves upon previous methods by optimizing parameters for better performance while reducing weight compared to existing systems that use multiple processors or threads simultaneously. It also allows for faster data analysis times due to its ability to be optimized over different dimensions (fourth dimension) at once. Overall, this new approach provides improved efficiency and accuracy in detecting road signage accurately across various resolutions.

Problems solved by technology

This patented technical problem addressed in this patents relates to improving the accuracy and speed at which identifying targets (target objects) within images captured with cameras or sensors becomes possible due to their high dimensionality compared to other types of imagery. Current techniques have limitations including slow response times caused by large amounts of time required for pixel values to transfer across different layers before being detected.

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