Abstract
With the advent of the 5G era, wireless network data transmission and real-time information acquisition face certain technical challenges. Simultaneously, how to ensure fast and safe information transmission becomes the research topic of the information age. The improvement of this research is based on the traditional fine-grained algorithm, and this study uses spatial constraints and evaluation scores to obtain the bounding box positions of objects and objects. Simultaneously, Part-based R-CNN is used to extract convolution features for each filtered bounding box and join the local features to form a feature representation vector. In addition, the research is based on the application of high-resolution acquisition of information entropy, abnormal signal detection and transient signal measurement methods and techniques in typical time domain test instruments, that is, digital oscilloscope, and this study is experimentally verified. The research indicates that the method proposed in this paper is scientific and can provide theoretical reference for subsequent related research.
Published Version
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