Systematic literature review of AI algorithms applied to unmanned aerial vehicle images

Abstract

ABSTRACT Artificial Intelligence (AI) combined with image processing has shown significant improvements through new techniques such as Machine Learning (ML) models. This paper introduces the key methods and algorithms used for Drone image processing. We discuss the benefits and limitations of using ML models instead of classical techniques. Our goal is to classify, categorize and describe the methods that are used in realistic settings of diverse domains of applications. We conducted a systematic literature review where systems presented in the papers were analysed based on their domain, task, technology, and efficiency. By extensively reviewing the existing literature, we successfully identified key themes and trends that emerged across the various research questions. The overall findings of the research emphasise the potential of AI and drone imagery in numerous fields. However, the review also uncovered several challenges that necessitate attention, such as issues related to data quality and the requirement for more advanced AI algorithms. The paper outlines significant innovations in the field and offers recommendations for future research directions. By highlighting cross-disciplinary insights, it delves into methodological approaches, exploring commonalities in AI algorithms and UAVs technologies.