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Insects play an important role in determining crop productivity and quality. Digital image processing can be used for insect identification. Deep learning has significantly outperformed conventional methods in the field of digital image processing in recent years. Researchers' top research concerns now centre on how to identify plant diseases and pests using deep learning technologies. This manuscript defines the issue of insect detection and makes a comparison on various conventional DL insect detection techniques with experimental study and summarizes the recent deep learning research on insect detection based on differences in network structure, along with the benefits and drawbacks of each approach. Common datasets are introduced, and the results of previous investigations are examined. In addition, possible solutions and research ideas are proposed for the challenges, and several suggestions are given. Finally, this study gives the analytics and prospect of the future trend of insect detection based on deep learning.
Kumar et al. (Thu,) studied this question.