Abstract

Rapid development of Artificial Intelligence (AI) technologies in recent years has created new opportunities to address the growing challenges in the aviation industry. Machine learning and Deep Learning, particularly through Convolutional Neural Networks (CNNs), have advanced image recognition capabilities, enhancing inspection processes possibilities. This paper explores the integration of AI with drones to improve the precision, efficiency, and speed of inspections of airframe emphasizing the necessity of accurate equipment preparation and precise operational planning. The study demonstrates how AI algorithms can process high-resolution images and sensor data to identify and classify defects. The motivation for this paper is to address the critical need for more efficient inspection methods in aviation, driven by the industry's increasing demand for higher repair process throughput and stringent safety standards.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.