Vision-Based Deep Q-Learning Network Models to Predict Particulate Matter Concentration Levels Using Temporal Digital Image Data

Figure 2

Shown are temporal differences between two consecutive arrays with regard to two scenarios (e.g., safe and harmful), respectively. The visual distinction of two difference arrays looks obvious in the sense that the harmful case generates explicit discordance as compared to the safe case.

(a) Safe

(b) Harmful