This research aims to improve target detection under challenging conditions like haze and low light.
Developed a simulation framework designed for smoke interference
Optimized recognition technology for use in low visibility environments
Tested effectiveness in various battlefield scenarios
Demonstrated improved detection rates in smoky conditions
Showed better performance compared to traditional methods
Reduced false positives in low visibility situations
Abstract
To address the limitations of traditional detection methods incomplex battlefield environments such as haze and night vision,a simulation and recognition framework optimised for smokeinterference is proposed.