Infrared Image Human Target Detection Method Based on Deep Learning

Introduction: In this study, we investigate human target detection techniques for infrared target recognition in complicated backdrops using deep learning approaches. This study uses the human target detection of infrared images in various scenes as its research object. Method: A test was conducted using MatlabR2010a and the real-time C language development platform. The findings indicate that, in the unoptimized case, the computing speed of the method was only 0.34 seconds. However, following optimization, its performance significantly increased to meet the real-time performance requirements. Result: The research findings presented in this work will be crucial to the relief and rescue efforts following engineering mishaps. Conclusion: This study is innovative in that it develops a deep learning-based model for human target detection in infrared photos and thoroughly examines and improves its functionality.