From identification to forecasting: the potential of image recognition and artificial intelligence for aphid pest monitoring.

ABSTRACT: Insect monitoring has gained global public attention in recent years in the context of insect decline and biodiversity loss. Monitoring methods that can collect samples over a long period of time and independently of human influences are of particular importance. While these passive collection methods, e.g. suction traps, provide standardized and comparable data sets, the time required to analyze the large number of samples and trapped specimens is high. Another challenge is the necessary high level of taxonomic expertise required for accurate specimen processing. These factors create a bottleneck in specimen processing. In this context, machine learning, image recognition and artificial intelligence have emerged as promising tools to address the shortcomings of manual identification and q

SUBMITTER: Batz P 

PROVIDER: S-EPMC10396399 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature