Image cutting in video media technology application based on detection algorithm

Abstract

Speech activity detection algorithm belongs to a kind of means to judge the audio section and non audio section. Audio information diagnosis is composed of audio and noise section, and special treatment means are used for different signals. In the real model test, we can understand that RBF core has super stable attributes compared with other models, and has good self-renewal ability. In the audio information discrimination attribute diagnosis, we can understand the upgrading calculation process, and understand the large-scale counting audio information discrimination calculation process. The removal of pictograph is the primary obstacle to the solution scope of visual information. In the real use process, the classi ed noises are stored in the image removal with different attributes on a large scale, which plays a great role in the gradual diagnosis of image removal such as image upgrade and image classi cation. Therefore, in order to update the image level, eliminate the noise object and gradually diagnose the image, exploring the image removal method has become the rst in uential step in the rst step of image diagnosis.. In the era of interconnection, we began to further explore the merging means model of interconnection, visualization and information interoperability, focusing on the governance of the merging and upgrading means model on the premise of interconnection, visualization and information interoperability, We can also apply multi-channel upgrading to upgrade our own hardware and software strength, observe and learn the quality level of the mode and class, so that the practical role of the means of mutual transmission of interconnected visual information can go on for a longer time.