3results about How to "Solve technical problems with low recognition accuracy" patented technology

The invention discloses an abnormal transaction identification method and device, a storage medium and electronic equipment. The method relates to the field of financial science and technology, and comprises the following steps: obtaining multi-modal data corresponding to a target transaction, and determining a target transaction scene corresponding to the target transaction according to the multi-modal data; under the condition that the target transaction scene is the first transaction scene, performing feature extraction processing on operation behavior data in the image data, the voice data and the environment data to obtain image features, voice features and operation behavior features; performing weighted fusion processing according to the image features, the voice features and the operation behavior features to obtain fusion data; and judging whether the target transaction is abnormal or not according to the fusion data and a preset threshold value corresponding to the target transaction scene, and obtaining a judgment result. Through application of the method and the device, the problem that the recognition accuracy is relatively low in a strong light environment and a face shielding scene due to the fact that abnormal transaction recognition depends on a single visual mode in related technologies is solved.

The application discloses a text processing method and device, a storage medium and a processor, and relates to the technical field of semantic recognition. The method comprises the following steps: obtaining an input text, wherein the input text comprises a plurality of input words; performing word segmentation on the input text to obtain an initial word segmentation result of the input text, wherein the initial word segmentation result comprises word segmentation probabilities of the plurality of input words, a first word segmentation label and a second word segmentation label, the first word segmentation label is used for representing a word segmentation label of the input text, and the second word segmentation label is used for representing a word segmentation label obtained after error correction processing is performed on a wrong word contained in the input text; selecting a target word segmentation label from the first word segmentation label and the second word segmentation label based on the word segmentation probabilities; and determining a target word segmentation result of the input text by using the target word segmentation label. The application solves the technical problem that the recognition accuracy of a word segmentation model is low due to wrong words in training samples.

This invention discloses a robot control method, an automatic cleaning device, and a storage medium. In this embodiment, after acquiring multiple frames of point cloud data collected by a line laser sensor, the automatic cleaning device first determines the object category corresponding to each point cloud dataset based on the point cloud features of the point cloud dataset within a preset distance range in each frame. Then, based on the object category of each point cloud dataset in each frame, it determines the target object category corresponding to each environmental object. Finally, it controls the automatic cleaning device to avoid obstacles based on the target object category. This invention, by determining the object category of the point cloud dataset within a preset distance range in each frame and determining the target object category based on the object category of each point cloud dataset in all frames, avoids the situation of identifying obstacles based solely on a single frame, thus improving the accuracy of obstacle identification.