2results about How to "Short sequence length" patented technology

This invention discloses a three-dimensional breast ABUS image classification method, electronic device, and computer-readable storage medium based on a tokenized bi-branch selective state-space model. The method preprocesses the three-dimensional ABUS volume data and inputs it into a hierarchical pyramidal classification network. The network constructs local convolutional branches and a global state-space branch in its basic modules: the local branch uses lightweight three-dimensional grouped convolution to extract texture and boundary morphology; the global branch aggregates features into a token map through voxel token generation, then performs multi-axis bi-directional selective state-space scanning and adaptive fusion using routing weights. After detoxing, the core features are injected through a gating mechanism. Finally, the classification result is output through three-dimensional global average pooling and a fully connected layer, enhancing the ability to model long-range dependencies across slices with near-linear complexity.

The application discloses a three-dimensional feature representation-based intelligent text reading comprehension method and device, a storage medium and an electronic device, and belongs to the fields of natural language processing and artificial intelligence; the technical problem to be solved by the application is how to capture direct interaction features between three-sequence data and how to enhance sufficient interaction among an article, a question and options, so as to improve the prediction accuracy of an intelligent text reading comprehension system; the technical scheme adopted is as follows: ① a three-dimensional feature representation-based intelligent text reading comprehension method, comprising the following modules: a pre-training embedding representation module, a feature filtering module, a 3D CNN interaction feature module and a label prediction module; ② a three-dimensional feature representation-based intelligent text reading comprehension device, comprising: an intelligent text reading comprehension data set acquisition unit, an intelligent text reading comprehension model construction unit and an intelligent text reading comprehension model training unit.