6results about How to "Reduce data transfer" patented technology

The application provides a kind of power grid equipment three-dimensional twin model slice simplification method based on visual relationship, belong to power grid three-dimensional visualization technical field, the method steps: the data format of power grid equipment three-dimensional model is unified and is parsed;Construct power grid equipment three-dimensional model object instantiation information;From model data, texture is compressed;Using octree structure is handled to model data slice and vertex optimization and monomer;According to octree structure, the model slice data after processing is merged, generates each level LOD;In three-dimensional network application end, according to the format requirement, the device and component instantiation of multiplexing are instantiated, load power grid equipment three-dimensional model in current window current level LOD data rendering.The application is compressed model vertex and texture data, multiplexing device and component instantiation, and load the LOD of current window, realizes the efficient transmission, loading and rendering effect of power grid equipment three-dimensional model data in the application without plug-in.

The present application relates to a kind of pneumonia detection model training method, specifically to a kind of hierarchical topology pneumonia detection model based on collaborative learning system and method.It overcomes the difficulty of existing pneumonia detection model training system, low efficiency and the problem that local detection node cannot achieve optimal detection performance.First, each node uses local pneumonia data to pre-train respective pneumonia detection model locally, then, center node is based on the feedback data of local model to build hierarchical topology collaborative learning system;After that, each cluster node and child node uses local pneumonia data to train respective pneumonia detection model locally;Finally, collaborative training is carried out, including intra-cluster collaborative training and inter-cluster collaborative training;Intra-cluster collaborative training includes cluster node aggregation training and child node random interactive training.The present application has small data transmission, storage and calculation pressure, and is easy to implement;At the same time, different client is provided with different model parameters, so that each hospital detection node achieves local detection performance maximization.

This invention relates to the field of robot control technology, specifically to an end-to-end closed-loop control method and system for robots based on multimodal perception fusion. It includes: a perception access layer for standardized access to data from multiple sensor types; a fusion processing layer for spatiotemporal alignment and multimodal fusion processing of the standardized access data; a decision control layer for generating execution instructions based on the fusion processing results; and an execution feedback layer for feeding back the execution status to the fusion processing layer to form closed-loop control. This technical solution can solve the problems of standardized access and real-time fusion of multi-source heterogeneous data, and construct a closed-loop control architecture with high fault tolerance and low latency.

This invention discloses a method, apparatus, device, and medium for updating a fundus image recognition model, relating to the field of ophthalmology. The method includes: determining a set of target features for the fundus image based on the acquired knowledge of fundus image recognition model samples corresponding to the user terminal to be updated; acquiring the activation values ​​of neurons in the recording network corresponding to each user terminal to be updated; constructing a local fundus image recognition model subgraph based on the fundus image recognition model sample knowledge, activation values, and a set of common features of the fundus image; transmitting all local fundus image recognition model subgraphs to a server; performing subgraph fusion on all the local fundus image recognition model subgraphs to obtain a fused subgraph; and updating the local fundus image recognition model using the fused subgraph. This invention transforms the fusion and updating of the user terminal model into an operation of subgraph fusion to generate a full image, ensuring privacy and security throughout the model fusion cycle based on multiple privacy computing technologies, and achieving secure model transmission and incremental fusion.

This invention relates to the field of rehabilitation data communication technology, specifically a method for integrated medical and educational multimodal data acquisition and analysis for autism rehabilitation. The method includes: constructing a set of multimodal data acquisition units; performing integrated autism rehabilitation data detection based on these units to obtain multimodal rehabilitation data; if the multimodal rehabilitation data contains anomaly tags, transmitting the data to the original receiving terminal via an emergency transmission channel to obtain the target receiving terminal; if the multimodal rehabilitation data does not contain anomaly tags, recording it as normal polling data; summarizing the normal polling data to obtain a normal polling dataset; and transmitting the normal polling dataset to the original receiving terminal to obtain the target receiving terminal. This invention can improve the accuracy of rehabilitation status monitoring and reduce the risk of missed reports of abnormal conditions.