Research on environmental adaptability of AI-based visual perception system under the perspective of vibration.

Artificial intelligence (AI) models are widely used in intelligent devices. However, challenging vibration environments can seriously affect the environmental adaptability of AI-based devices. In this paper, an environmental adaptability assessment method of AI-based devices is proposed. The formation mechanism of optical blurred image is elaborated, and measure function is used to transform the stress magnitudes of environment into distances of distribution discrepancy. To ensure that the obtained optical blurred images are fully controllable, we generate vibration-blurred images using an explicitly quantifiable extended dataset. Additionally, the generated vibration-blurred image is evaluated for consistency with the actual image. Finally, the environmental adaptability of multiple state-of-the-art models is evaluated based on extended datasets. The assessment results show that the environmental adaptability of the visual perception system is mainly limited by the vibration amplitude under high frequency. Under low frequency vibration, the environmental adaptability of AI models is also frequency-dependent. [ABSTRACT FROM AUTHOR]