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This article aims to review the applications and development trends of deep learning in drone target detection. First, it introduces the current state of drone technology and deep learning technology, as well as their wide range of application areas. Then, it explains the relationship between artificial intelligence, machine learning, neural networks, and deep learning, focusing on the advantages of deep learning in drone target detection. Next, it provides a detailed analysis of the basic principles and representative models of single-stage and two-stage target detection algorithms in deep learning and a performance comparison of these models on drone datasets. Finally, through examples of agricultural monitoring, disaster relief, environmental monitoring, and infrastructure inspection, it demonstrates the specific effectiveness of deep learning models in drone applications.

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The Development, Application, and Future Trend of Deep Learning in UAV Target Recognition

  • 会议论文

  • 发表日期：

    2025年

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  • Longhao Tang,
  • Xiaoxu Sun

摘要

This article aims to review the applications and development trends of deep learning in drone target detection. First, it introduces the current state of drone technology and deep learning technology, as well as their wide range of application areas. Then, it explains the relationship between artificial intelligence, machine learning, neural networks, and deep learning, focusing on the advantages of deep learning in drone target detection. Next, it provides a detailed analysis of the basic principles and representative models of single-stage and two-stage target detection algorithms in deep learning and a performance comparison of these models on drone datasets. Finally, through examples of agricultural monitoring, disaster relief, environmental monitoring, and infrastructure inspection, it demonstrates the specific effectiveness of deep learning models in drone applications.