The invention discloses an image recognition method based on an improved Focal
loss function, and the method comprises the steps: improving a
modulation factor of the Focal
loss function on the basis of an existing Focal
loss function, enabling the function to have higher attention to a difficult sample, and enabling the function to have relatively lower attention to a
simple sample; and then, on the basis of the
convolutional neural network model based on the Focal loss function, predicting the residual
negative sample set, screening all difficult samples, dividing the samples into N equal parts, respectively adding the N equal parts into the original
training set to form N new training sets, then training a plurality of models, and determining a final prediction picture
label result according to voting selection of the N models. According to the method, on the basis of an original Focal loss function, the attention degree on a difficult sample is higher, and the model generalization ability is improved; and under the condition of excessive negative samples, difficult samples are screened out by utilizing the original model and added into the
training set, so that the accuracy of the model is improved, available samples are fully utilized, and the calculation amount during model training is also reduced.