Visual computing resources distribution and balancing by multimodal cat swarm optimization
作者：
Highlights：
• We proposed a novel multi-view cat swarm optimization algorithm to optimize the assignment of each visual data to the appropriate remote server.
• An intelligent multi-channel feature fusion algorithm that automatically calculates the importance of each feature channel.
• Comprehensive experimental evaluation to testify the competitiveness of our MSCO toward the state-of-the-art clustering-based optimization framework.
摘要
•We proposed a novel multi-view cat swarm optimization algorithm to optimize the assignment of each visual data to the appropriate remote server.•An intelligent multi-channel feature fusion algorithm that automatically calculates the importance of each feature channel.•Comprehensive experimental evaluation to testify the competitiveness of our MSCO toward the state-of-the-art clustering-based optimization framework.
论文关键词：Visual computing,Resources distribution,Multi-view feature fusion,Cat swarm optimization,Mixture ratio
论文评审过程：Received 27 June 2019, Revised 16 February 2020, Accepted 1 March 2020, Available online 8 April 2020, Version of Record 28 April 2020.
论文官网地址：https://doi.org/10.1016/j.image.2020.115816
