WiMi Hologram Cloud Inc. announced that it developed a swin-transformer and hash-based on-chain copyright detection technology, which not only improves the efficiency and accuracy of copyright detection, but also provides a new solution for copyright protection through blockchain technology. This not only helps protect the legitimate rights and interests of creators, but also provides strong support for the healthy development of the entire video content industry. The technological innovation of WiMi's swin-transformer and hash-based on-chain copyright detection technology is reflected in the following aspects: Application of deep learning: Swin-Transformer is an advanced deep learning model that has excellent performance in image recognition and video analysis.

Compared with traditional copyright detection methods, Swin-Transformer is able to recognize the features of video content more accurately and improve the accuracy of copyright detection. In addition, it can handle large-scale video data, making the copyright detection process more efficient. Combination of hashing algorithm: Hashing algorithm is used to generate unique fingerprints or identifiers of video content.

These hash values demonstrate the key features of the video and remain consistent even after the video is compressed or edited. This enables copyright detection to recognize not only identical copies of videos, but also infringing videos that have been modified. Integration of blockchain: The utilization of blockchain technology has revolutionized video copyright detection.

By storing the hash value of the video on the blockchain, the immutability and permanence of this data can be ensured. In this way, once the video content is verified as original, its copyright information can be permanently recorded and protected and cannot be changed or deleted by anyone. Automation of smart contracts: Smart contracts are self-executing programs on the blockchain that can automatically perform predetermined actions when specific conditions are met.

In video copyright detection, smart contracts can automatically verify the originality of video content and record the detection results. This automation not only improves the efficiency of the detection process, but also reduces the possibility of human error. Optimization of block comparison: Traditional video comparison methods usually need to analyze the whole video file, which is very time-consuming when dealing with large amounts of data.

Instead, the swin-transformer and hash-based on-chain copyright detection technology adopts block comparison approach to quickly identify similarities by comparing different parts of the video. This approach greatly reduces the time and computational resources required for comparison. WiMi's swin-transformer and hash-based on-chain copyright detection technology has significant technical advantages.

Firstly, it realizes efficient and accurate analysis of video content by combining the deep learning model swin-transformer, which can capture the details and patterns in the video to extract representative feature vectors. These feature vectors not only accurately reflect the uniqueness of the video content, but also quickly match similar or identical content in large-scale video databases. In addition, the adaptive capability of the deep learning model means that the accuracy and efficiency of the detection system will continue to improve as more data is fed into it, which is crucial for handling the large amount of video content that is constantly emerging on the web.

Second, the technology uses a deep hashing algorithm to generate unique fingerprints of video content that remain consistent even after the video has been compressed, cropped, or otherwise edited. This consistency ensures that the system is able to accurately recognize original content even when confronted with modified infringing videos. At the same time, these hash values are stored on the blockchain, utilizing the blockchain's immutability to protect video copyrights.

This storage method not only guarantees the security of copyright information, but also makes the copyright verification process transparent and traceable, greatly enhancing the credibility of copyright protection. In addition, the technology further enhances the efficiency and responsiveness of copyright detection through the automation function of smart contracts. Smart contracts are able to perform the copyright detection and verification process automatically on the blockchain without human intervention, thus reducing processing time and potential human errors.

In addition, the block comparison approach enables the system to quickly compare different parts of the video rather than the entire video file, which greatly improves the comparison speed and reduces the consumption of computing resources. This efficient detection mechanism is not only applicable to the current scale of video content, but can also adapt to future growth in video data volume, providing a sustainable solution for copyright protection. The promotion and application of this technology signals a more intelligent, efficient and transparent future for copyright protection.

With the continuous progress and optimization of the technology, it will facilitate a more just and reasonable digital copyright ecosystem. It not only provides solutions to current copyright protection problems, but also points out the direction of future copyright protection trends. The wide application of this technology will lead to the arrival of a more prosperous and orderly digital creative era.