Method and Apparatus for training an object recognition model

A device, comprising

• at least one processor;
• and
• at least one storage device on which instructions are stored, the instructions, when executed by the at least one processor, causing the at least one processor to perform a method for training a neural network model for object recognition, comprising:
• determining loss data for features extracted from a training image set using the neural network model and a loss function with a weight function, and
• performing an updating operation for parameters of the neural network model based on the loss data and an updating function,
• wherein the updating function is derived based on the loss function with the weight function of the neural network model, and the weight function and the loss function change monotonically in a specific value interval in the same direction.