An aggregation cross-entropy loss function-based sequence recognition method comprises the following steps: downloading natural scene text recognition data as a test set, and using data of natural scene text synthesized by using open source code as training data; acquiring an image in a natural scene, and performing normalization on the image; count character classes appearing in a label in the image and obtain the occurrence counts of the character classes; predicting, by means of a supervision network, character classes and occurrence counts of the character classes in natural scene text data, and performing training with respect to portions that differ between the natural scene text data and the label; inputting the natural scene text recognition data in step A and label data in step C into a pre-designed network and performing training; and inputting test data into the trained network, and finally obtaining a recognition result of the image. The invention achieves superior robustness and effectiveness for text not arranged in a straight line.
AGGREGATION CROSS-ENTROPY LOSS FUNCTION-BASED SEQUENCE RECOGNITION METHOD