Advances in Computer Vision technology paved the way for the development of production pipelines which proved to perform similarly to human operators in terms of accuracy and better then them in terms of time, when applied on repetitive analysis. These performances increase with the introduction of Deep Learning algorithms, which narrow the margin with human level behavior. This Thesis work focuses on Deep Learning approaches for a Computer Vision application in the Passive Safety checks field. In particular, the description of a tool aimed at checking the correct deployment of airbag devices is provided, delving into the Deep Learning-based detection engine.