Generating Simulated Infrared Sensor Images Using Deep Learning Neural Networks
Year: 2025
Type: conference-paper
Abstract: This study presents a method for generating infrared images using deep learning techniques, specifically Generative Adversarial Networks (GANs), trained on data from real flight experiments. Implemented in Python, the approach leverages a U-Net adapted for gray-scale IR image generation. After training on a multi-core computer, the method achieved accurate infrared image generation, applicable in flight simulation and autonomous navigation.
Source: elib (German Aerospace Center)
DOI: 10.25967/650013
Author: Peinecke, N.
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7094947565
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