关键词: 图像情感分析, 情感图像数据集, 卷积神经网络, 样本不平衡, Focal损失函数

Abstract:

Focal loss function, which has the characteristics of mining hard example and alleviating the imbalance problem of training data, is applied to the image emotion analysis model based on neural network in this paper. To alleviate the data imbalance problem in the training data set and improve the training efficiency of the emotion classification model, the parameters in Focal loss function are modified. The balance parameter [α] is decided by class weight value, and the focal parameter [γ] is modified in the different stage of training. Then the modified Focal loss is used in the training of emotion image analysis model. The experimental results show that the modified Focal loss function can improve the performance of emotion image analysis model, and the accuracy, the macro recall and the macro precision of model are promoted by 0.5-2.3 percentage points, 0.4-3.9 percentage points, 0.5-3.3 percentage points respectively.

Key words: image emotion analysis, image emotion data set, convolutional neural network, data imbalance, Focal loss function