Abstract
Aiming at the problem that it is difficult to distinguish the authenticity of a large number of eyewitness reports when Asian giant hornet invaded, a multi-scale comprehensive detection model of Asian giant hornet was designed. The model uses cellular automata to process geographical information, YOLOv3 and improved Resnet101 to process image information, TF-IDF and Linear SVC to process textual information, and fuses the three kinds of information with a certain weight to obtain the final detection probability of Asian giant hornet. Compared with a single detection algorithm, this model makes use of multi-scale and multi-class information, and has higher classification accuracy and better robustness.
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