Russian Neural Network Can Now Spot Vehicles in Low Visibility

Engineers in Moscow have trained a neural network to accurately recognize vehicles even in poor lighting or low-quality video—potentially transforming traffic control and logistics.

Russian scientists have developed a neural network that can identify vehicles under challenging visual conditions. According to Izvestia, the system uses a technology called LightHead, created by researchers at the Moscow Technical University of Communications and Informatics.

The AI model can distinguish cars from other moving objects, such as birds, and differentiate between passenger and commercial vehicles. It performs well in low frame-rate video, poor lighting, and even on devices with limited computing power.

Although the system has not yet been tested in real-world settings, developers have high hopes. Beyond traffic law enforcement, the neural network is expected to support logistics applications by helping identify optimal routes during high traffic congestion.

The breakthrough represents another step toward smarter, AI-driven infrastructure solutions in Russia’s transportation sector.