WiMi Hologram Cloud Develops Neural Network-Based Data Fusion Algorithm System to Boost Processing Capacity

Rhea-AI Summary

WiMi Hologram Cloud (NASDAQ: WIMI) has announced the development of a neural network-based data fusion algorithm system aimed at enhancing information processing capabilities. This technology integrates multi-dimensional data, improving speed and accuracy while reducing redundant transmissions. The neural network, characterized by its self-learning abilities and fault tolerance, processes inputs from various sensors to establish a cohesive understanding of complex data. This advancement positions WiMi to leverage AR technology more effectively and cater to the growing demands within the holographic sector.

Positive

• Development of a neural network-based data fusion algorithm system to enhance processing capabilities.
• Improved speed and accuracy of information processing through advanced neural network technology.
• Enhanced self-learning and fault tolerance characteristics of the system.

Negative

• None.

BEIJING, March 1, 2023 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the development of neural network-based data fusion algorithm system. Data fusion is the integrated processing and optimization of multi-dimensional information acquisition, representation, and intrinsic linkages to produce complete, accurate, timely, and effective integrated information.

With powerful self-learning, adaptive, non-linear matching, and information processing capabilities, neural networks are algorithms that imitate human brains for information processing. Applying neural network technology to data fusion can reduce redundant data transmission and improve the system's speed, accuracy, and performance.

Neural networks usually consist of an input layer, a hidden layer, and an output layer. The multi-layer network architecture makes the output of information more accurate. The neural network algorithm is a supervised learning algorithm whose main idea is to learn from known network intrusion samples by using gradient search techniques, with the ultimate goal of minimizing the mean square error between the actual output value of the network and the desired output value. In addition, neural networks provide non-linear transfer functions and parallel processing capabilities to help perform image fusion. The neural network consists of processing nodes (neurons) connected. A neural network data fusion model is built to assign neurons and interconnect weights based on the relationship between the input and output of multi-sensor data.

Neural networks have robust characteristics such as fault tolerance and self-learning, self-organizing and self-adaptive capabilities. The system's classification criteria are determined based on the similarity of the samples accepted. The weight distribution of the network characterizes the process. Specific neural network algorithms are also used to acquire knowledge, obtain uncertainty inference mechanisms, and utilize neural networks' signal processing capabilities and automatic inference functions to achieve multi-sensor data fusion.

Firstly, the system chooses its topology according to the requirements and the form of sensor information fusion. Secondly, the input information of each sensor is integrated and processed by the system into an overall input function, and this function mapping is defined as the mapping function of the relevant units. The statistical laws of the environment are reflected in the network's structure through the interaction between the neural network and the environment. Finally, the system learns and understands sensor output information, determines the assignment of weights, completes the fusion of knowledge acquisition information, interprets patterns, and converts the input data vectors into high-level logical concepts.

WiMi's system utilizes the generalization ability of neural networks and pattern recognition. It can deal with uncertain information as classifiers, fuse the sensor information obtained by the network, get the parameters of the corresponding network, convert the knowledge rules into digital form, and establish a data knowledge base. The system can acquire knowledge by extracting external information and parallel associative reasoning. The complex relationships of the uncertain environment are fused into accurate signals that the system can understand after learning and reasoning. Neural networks have the capability of massively parallel processing of information, which can enhance the speed of information processing in the data fusion algorithm system, effectively reduce redundant data transmission, increase the accuracy of data fusion, and improve the performance of the data fusion algorithm. At the same time, the distributed information storage and parallel processing features of the neural network are used to achieve real-time recognition and improve the performance of the data recognition system.

About WIMI Hologram Cloud

WIMI Hologram Cloud, Inc. (NASDAQ:WIMI), whose commercial operations began in 2015, is a holographic cloud comprehensive technical solution provider that focuses on professional areas including holographic AR automotive HUD software, 3D holographic pulse LiDAR, head-mounted light field holographic equipment, holographic semiconductor, holographic cloud software, holographic car navigation and others. Its services and holographic AR technologies include holographic AR automotive application, 3D holographic pulse LiDAR technology, holographic vision semiconductor technology, holographic software development, holographic AR advertising technology, holographic AR entertainment technology, holographic ARSDK payment, interactive holographic communication and other holographic AR technologies.

Safe Harbor Statements

This press release contains "forward-looking statements" within the Private Securities Litigation Reform Act of 1995. These forward-looking statements can be identified by terminology such as "will," "expects," "anticipates," "future," "intends," "plans," "believes," "estimates," and similar statements. Statements that are not historical facts, including statements about the Company's beliefs and expectations, are forward-looking statements. Among other things, the business outlook and quotations from management in this press release and the Company's strategic and operational plans contain forward−looking statements. The Company may also make written or oral forward−looking statements in its periodic reports to the US Securities and Exchange Commission ("SEC") on Forms 20−F and 6−K, in its annual report to shareholders, in press releases, and other written materials, and in oral statements made by its officers, directors or employees to third parties. Forward-looking statements involve inherent risks and uncertainties. Several factors could cause actual results to differ materially from those contained in any forward−looking statement, including but not limited to the following: the Company's goals and strategies; the Company's future business development, financial condition, and results of operations; the expected growth of the AR holographic industry; and the Company's expectations regarding demand for and market acceptance of its products and services.

Further information regarding these and other risks is included in the Company's annual report on Form 20-F and the current report on Form 6-K and other documents filed with the SEC. All information provided in this press release is as of the date of this press release. The Company does not undertake any obligation to update any forward-looking statement, except as required under applicable laws.

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SOURCE WiMi Hologram Cloud Inc.

FAQ

What is the recent development by WiMi Hologram Cloud?

WiMi Hologram Cloud has developed a neural network-based data fusion algorithm system to enhance information processing capabilities.

How does the neural network-based system improve data processing for WIMI?

The system reduces redundant data transmission and improves speed and accuracy in handling multi-dimensional sensor data.

What are the key features of WiMi's neural network technology?

Key features include self-learning capabilities, fault tolerance, and improved performance in data fusion and recognition.

When was the announcement made regarding WIMI's new technology?

The announcement was made on March 1, 2023.

What impact does the new data fusion algorithm have on WIMI's services?

It enhances WiMi's ability to provide accurate and timely integrated information, benefiting their holographic AR technologies.