Design of a Deep Neural Network-Based Visual Data Processing System for Digital Media Optimization Applications

Abstract

Multimedia information processing is a universal technical demand in smart life, especially in applications of digital media optimization. However, there still lacks mature design of reliable visual data processing systems for this area. Because digital media interaction is featured with high dynamics and large business amount, which poses high requirement for processing ability and efficiency. To deal with this issue, this paper presents design of a deep neural network-based visual data processing system for digital media optimization applications. First of all, an overall mechanism algorithm that coordinates automatic workflow of the whole system is designed. Then, a BP neural network structure is adopted to realize intelligent resource classification according to different user behaviors and user preference. Through the strong ability of information processing brought by deep neural network, business scheduling and operation in digital media applications can be optimized. As for evaluation, the designed deep neural network is compared with a traditional vision processing algorithm to test the processing efficiency of visual data. The obtained results can reflect that the designed visual data processing system can work well in digital media optimization applications.

Keywords

• Deep learning
• vision computing
• multimedia systems
• business scheduling