2results about How to "Increase compression" patented technology

This invention relates to the field of data processing technology, specifically to a blockchain-based method and apparatus for storing civil engineering test data. The method includes: acquiring civil engineering test data stored on the blockchain and real-time collected civil engineering test data, and preprocessing it to obtain analysis data; determining the importance, access frequency, and final repetition rate of character data based on the analysis data, and obtaining the encoding priority of the character data, adjusting the Huffman coding table; compressing all civil engineering test data according to the adjusted Huffman coding table, and re-storing it in the blockchain; and comprehensively adjusting the Huffman coding table based on the obtained encoding priority of each character data, compressing the data, and re-storing it in the blockchain. This method reduces the amount of data while maintaining access speed, thereby improving the reading speed for high-access data during subsequent data access.

The application discloses a video anomaly detection method based on clustering guided learning, comprising the following steps: the method designs an efficient and excellent video automatic encoder on the basis of a U-Net framework, the encoder replaces convolution operation with self-attention operation based on a Swin Transformer (ST) to better capture image frame information, the U-Net self-encoder structure deletes the skip connection layer structure therein, the convolution structure is replaced with a Swin Transformer module, and the patch embed structure under the Swin Transformer framework is added to the encoder part to reduce the calculation amount; the learning ability and convergence speed of the ST framework are enhanced by using an I3D Block. Meanwhile, a double-scale deep clustering module is designed to compress and represent the feature information and spatial structure information of the image frame, and the generalization ability of the encoder is well limited. In addition, the model provides two kinds of anomaly detection methods of reconstruction and prediction.