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WiMi to Develop A Multimodal Information Fusion Detection Algorithm Based on GANs

WIMI

BEIJING, June 12, 2023 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that it is developing a multimodal information fusion detection algorithm based on generative adversarial networks(GANs). The multimodal information fusion detection algorithm is a method to improve detection accuracy and robustness by fusing data from different sensors or modalities using a GAN. It is implemented by training two neural networks, a generator and a discriminator, where the generator is responsible for generating false data samples, and the discriminator is responsible for distinguishing between accurate and inaccurate data. The two networks compete with each other for learning until the generator can produce sufficiently realistic data, and the discriminator cannot differentiate between true and false.

In multimodal information fusion detection, data from different sensors or modalities, such as image, sound, and text, can be fused and processed to obtain more comprehensive and accurate detection results. The generator uses local detail features and global semantic features to extract source image details and semantic information. Perceptual loss is added to the discriminator to make the data distribution of the fused image consistent with the source image, which improves the accuracy of the fused image. The fused features enter the interest pool network for coarse classification, the generated candidate frames are mapped to the feature map, and finally, the fully connected layer completes the target classification and localization.

GANs have inherent advantages in image generation, allowing unsupervised fitting and approximation of accurate data distributions. Using generators and discriminators for adversarial purposes allows fused images to retain richer information, and the end-to-end network structure no longer requires the manual design of fusion rules.

The technical process of the GANs-based multimodal information fusion detection algorithm studied by WiMi includes data preprocessing, GANs model training, model testing, result evaluation, and optimization and improvement. Data from different sensors or modalities, such as image, sound, and text, are fused for fusion processing, improving target detection accuracy and robustness. In addition, the end-to-end trained GANs can enhance the complementarity and redundancy between multimodal information features after fusing them to improve the accuracy of target detection and classification based on fused elements.

The multimodal information fusion detection algorithm treats the whole image fusion process as adversarial between a generator and a discriminator. For each modality, a generator and a discriminator can be trained separately. Then, by combining the generated results of multiple modalities, a more accurate and comprehensive detection result can be obtained.

Multimodal information fusion detection algorithm based on GANs is one of the fast-developing research directions in recent years. Much related research has been applied in different fields, such as intelligent surveillance, speech recognition, medical image analysis, industrial inspection, etc.

In the future, WiMi will further explore how to fuse more sensors and modalities to improve the fusion effect and applicability range. At the same time, WiMi will investigate how to adopt more efficient GAN structures and enhance model performance through more effective training methods. In addition, WiMi also considers combining this technique with deep learning to improve the accuracy and robustness of detection further. In conclusion, the multimodal information fusion detection algorithm based on GANs has many application prospects and is a research direction worthy of attention and in-depth study.

About WIMI Hologram Cloud
WIMI Hologram Cloud, Inc. (NASDAQ:WIMI) 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.

Cision View original content:https://www.prnewswire.com/news-releases/wimi-to-develop-a-multimodal-information-fusion-detection-algorithm-based-on-gans-301848057.html

SOURCE WiMi Hologram Cloud Inc.



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