Abstract: The present disclosure provides a method for visual question answering, which relates to fields of computer vision and natural language processing. The method includes: acquiring an input image and an input question; detecting visual information and position information of each of at least one text region in the input image; determining semantic information and attribute information of each of the at least one text region based on the visual information and the position information; determining a global feature of the input image based on the visual information, the position information, the semantic information, and the attribute information; determining a question feature based on the input question; and generating a predicted answer for the input image and the input question based on the global feature and the question feature. The present disclosure further provides a device for visual question answering, a computer device and a medium.

Abstract: This application discloses a method, an apparatus and an electronic device for error correction of numerical contents in a text, and relates to a technology field of artificial intelligence such as natural language processing and deep learning. The implementation method is: obtaining a target text to be processed; determining original numerical contents included in the target text; determining target types corresponding to the original numerical contents; and performing error correction on each original numerical content according to an error correction manner corresponding to each target type. Therefore, the error correction of numerical contents is realized according to types of the numerical contents, which is not only limited to the error correction of the numerical format, but also the logical error correction of the numerical content, so as to improve the numerical error correction capability and thereby improving the recall rate of detection and correction of wrong values.