The Analysis of Intelligent Real-Time Image Acquisition System Based on Data Mining

Abstract

The purpose is to enhance the timeliness of news, provide real-time news for the audience, and attract more traffic for the news media, thereby helping news media grow financially and strengthening the network security communication efficiency and accuracy. First, an intelligent real-time image acquisition system is introduced, and its principle and advantages are analyzed. Second, an intelligent real-time image acquisition model based on DL (Deep Learning) algorithm is established by combining DM (Data Mining) technology. Finally, the application of an intelligent image acquisition system in network communication is adjusted. The research results show that the combination of DL intelligent real-time image acquisition system with DM technology can effectively deal with various network communication scenarios, enhancing the accuracy and timeliness of network communication. The AlexNet model performs excellently in all aspects, with or without data enhancement or equalization. The recognition rate reaches 99.6% after data equalization and enhancement, and the AlexNet model can accurately classify news and non-news sceneries. This shows that the application of an intelligent real-time image acquisition system based on DM technology can effectively enhance the real-time performance of network communication. The results set an example for the application of relevant intelligent image acquisition technology in the journalism industry.