WiMi Hologram Cloud Inc., a leading global Hologram Augmented Reality (AR) Technology provider, announced that it developed model autonomous generation system based on three-dimensional intelligent algorithm is a system that uses artificial intelligence technology for three-dimensional modeling and image processing. The system can analyze the data by deep learning, extract features from it, and automatically help users generate 3D models and images that meet the requirements.
The system adopts a distributed architecture and consists of multiple subsystems. Each subsystem has clear functions and responsibilities and works together to provide users with high-quality 3D model and image generation services. The advantage of this architecture is that the subsystems can be flexibly expanded and upgraded, which improves the reliability and scalability of the whole system, and can satisfy users of different sizes and needs. Specifically, the system contains the following subsystems:
Data acquisition subsystem: This subsystem is responsible for collecting, organizing and storing raw data from various data sources, as well as pre-processing and cleaning the data. The data acquisition subsystem needs to support a variety of data types and formats, such as 3D modelling data, image data, etc., and be able to transform the data into a unified format for storage and management, to improve the accuracy and stability of subsequent model training and image generation. At the same time, the subsystem also takes into account factors such as data security and privacy protection.
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Model training subsystem: This subsystem is the core part of the whole system, which is responsible for using deep learning algorithms to analyze the collected data, analyze the data features and adaptively adjust the model parameters to achieve high-precision recognition and prediction of the sample data, and then train the model. The model training subsystem needs to take into account factors such as data volume, model structure and training time, and also performs model validation and evaluation.
Data management subsystem: This subsystem is responsible for the management and maintenance of collected data, model parameters, generated results and other information, including data storage, backup, recovery, version control, access control and so on. The data management subsystem needs to have high availability, high scalability and high security.
Data Visualization Subsystem: Data visualization can help users better understand and use the system by presenting the generated 3D models and images in an intuitive form through graphical interfaces and other means.
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System security subsystem: In practical applications, system security is very critical. The system needs to take a variety of measures to ensure data security, privacy protection and system stability. For example, encrypted communication, access control, security logging and other technical means can improve the security and reliability of the system.
These subsystems communicate with each other through interfaces and share data and resources. Each subsystem runs in a separate container and can be deployed and upgraded independently to achieve system reliability and scalability. Also, using a distributed architecture improves system concurrency and performance, and reduces the impact of system failures on the overall system.
Compared with the traditional 3D autonomous generation system, WiMi‘s system has the advantages of high efficiency, accuracy, and scalability, etc. It utilizes intelligent algorithms and distributed computing technology, which can efficiently process a large amount of data, and at the same time use deep learning algorithms to train and analyze the data, extract the features and generate high-quality 3D models and images, which can satisfy the various needs of users for the models and images, and can be used to generate 3D models and images in line with the parameters input by users. It can meet the various needs of users for models and images, and can autonomously generate 3D models and images that meet the requirements based on the parameters input by the users, which reduces the cost of manual intervention and time, and improves the efficiency and convenience of work. In addition, the system adopts a distributed architecture, consisting of multiple subsystems, each of which runs independently in a container, enabling faster, more flexible and more reliable expansion of the system. In addition, the system adopts a variety of security technologies, such as encrypted communication, access control, and secure logging, to ensure the security and privacy protection of user data.
The system has a wide range of application scenarios involving 3D modelling, image processing, virtual reality, game development and other fields. For example, the system can be used in industrial design, architectural design, medical image analysis, map production, animation production, etc. It helps to be able to quickly generate high-precision 3D models and images, and promotes product innovation and productivity improvement. In addition, it can be used in education, entertainment, culture and other fields to provide users with immersive and diverse experiences.
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