Training method and device of unmanned aerial vehicle individual identification model and computer equipment

The invention relates to a training method of an unmanned aerial vehicle individual identification model. The method comprises the steps of obtaining sample set information; training the initial single-head convolutional neural network model based on the sample set information, and extracting model parameters of a preset network layer from model parameters of the trained single-head convolutional neural network; constructing an initial multi-head convolutional neural network model based on a preset network layer and a target full-connection layer, wherein the target full-connection layer comprises a plurality of sub-connection layers in one-to-one correspondence with the unmanned aerial vehicle types; and for each unmanned aerial vehicle type, training the sub-connection layer corresponding to the unmanned aerial vehicle type through the sample information corresponding to the unmanned aerial vehicle type to obtain an unmanned aerial vehicle individual identification model. According to the method, the model