  In the current computer vision era classifying scenes through video
surveillance systems is a crucial task. Artificial Intelligence (AI) Video
Surveillance technologies have been advanced remarkably while artificial
intelligence and deep learning ascended into the system. Adopting the superior
compounds of deep learning visual classification methods achieved enormous
accuracy in classifying visual scenes. However, the visual classifiers face
difficulties examining the scenes in dark visible areas, especially during the
nighttime. Also, the classifiers face difficulties in identifying the contexts
of the scenes. This paper proposed a deep learning model that reconstructs dark
visual scenes to clear scenes like daylight, and the method recognizes visual
actions for the autonomous vehicle. The proposed model achieved 87.3 percent
accuracy for scene reconstruction and 89.2 percent in scene understanding and
detection tasks.
