Dongguan University of Technology

Harbin Institute of Technology (shenzhen) (shenzhen Institute of Science and Technology Innovation, Harbin Institute of Technology)

Ye Ding

Qing Liao

Binxing Fang

Xuan Wang

The present disclosure provides a multimodal fine-grained mixing method and system, a device, and a storage medium. The method includes: extracting data features from multimodal graphic and textual data, and obtaining each composition of the data features, the data features including a visual regional feature and a text word feature; performing fine-grained classification on modal information of each composition of the data features, to obtain classification results; and performing inter-modal and intra-modal information fusion on each composition according to the classification results, to obtain a fusion feature. The method enables a multimodal model to utilize a complementary characteristic of the multimodal data, with no influence by irrelevant information.

Multimodal fine-grained mixing method and system, device, and storage medium

The present disclosure provides an anomaly detection method and apparatus for multi-type data. According to the anomaly detection method for multi-type data, an adversarial learning network is trained, so that a generator in the adversarial learning network fits a distribution of a normal training sample and learns a potential mode of the normal training sample, to obtain an updated adversarial learning network, an anomaly evaluation function in the updated adversarial learning network is constructed according to a reconstruction error generated during training, and the updated adversarial learning network is constructed into an anomaly detection model, to perform anomaly detection on inputted detection data by the anomaly detection model, to obtain an anomaly detection result. A mode classifier is introduced to effectively resolve difficult anomaly detection when a distribution of detected data is similar to that of normal data, further improving the accuracy of anomaly detection.

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Guangdong, China

Ye Ding