Swarm Filter - A Simple Deep Learning Component Inspired by Swarm Concept

Abstract

Swarm is a research topic not only of biologists but also for computer scientists for years. With the idea of swarm intelligence in nature, optimal algorithms are proposed to solve different problems. In addition to the proactive aspect, a swarm can provide useful hints for identification problems. There are features that only exist when an individual belongs to a swarm. An idea came to us, deep learning networks have the ability to automatically select features, so they can extract the characteristics of a swarm for identification problems. This is a new idea in the combination of swarm characteristic with deep learning model. The previous studies combined swarm intelligence with neural networks to find the optimal parameters and architecture for the model. When performing our experiments, we were surprised that this simple architecture got a state-of-the-art result. This interesting discovery can be applied to other tasks using deep learning.