Loss function:
In deep learning, the loss function plays a vital role. By minimizing the loss function, the model can reach a state of convergence and the error of the model's predicted value can be reduced. Therefore, different loss functions have a significant impact on the model. Commonly used loss functions:
Image classification: Cross entropy
Target detection: Focal loss, L1/L2 loss function, IOU Loss, GIOU, DIOU, CIOU
Image recognition: Triplet Loss, Center Loss, Sphereface, Cosface, Arcface
Summary of the loss function of deep learning : This article introduces the above loss functions. After reading it, you can roughly understand the role of each loss function and the reasons for its occurrence.