Research and Application of Digital Media Object Classification Method Based on Large Interval Distribution Learning
- Resource Type
- Conference
- Authors
- Pu, Li'e; Ru, Huasuo; Tang, Yufang
- Source
- 2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON) Smart Generation Computing, Communication and Networking (SMART GENCON), 2023 3rd International Conference on. :1-5 Dec, 2023
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Deep learning
Computer aided instruction
Distance learning
Simulation
Media
Classification algorithms
Complexity theory
arge interval distribution learning
digital media
object classification
Classification algorithm
- Language
Digital media object classification plays an important role in digital media, but there is a problem of low classification accuracy. Deep learning algorithms cannot improve the accuracy of digital media object classification. Therefore, this paper proposes a large-interval distribution learning algorithm to classify digital media objects. Digital media objects are analyzed through distributed learning, and indicators are divided according to classification requirements. The large interval distribution learning algorithm forms the digital media object classification scheme, and the formed classification scheme is comprehensively analyzed. The simulation results show that the classification accuracy and classification efficiency of the proposed algorithm are better than those of the deep learning algorithm.