WiMi Hologram Cloud Inc. (NASDAQ: WIMI) (“WiMi” or the “Company”), a leading global Hologram Augmented Reality (“AR”) Technology provider, today announced that its R&D team is working on a multi-view based data fusion algorithm, powered by the multi-view learning algorithm.
The multi-view learning algorithm consists of co-training, multi-core learning, and subspace learning. The co-training algorithm considers that each sample can be divided into different views, with the option of maximizing the likelihood that both sides agree on the data in the different views. Multi-core learning involves a series of machine learning methods that use a core that naturally responds to other views, fusing linear and non-linear features together to improve learning. Subspace learning aims to obtain a subspace that different views can share. Through this subspace, subsequent tasks, such as classification and clustering, can be accomplished.
Data fusion algorithms and their applications continue advancing as technology iterates. Data has become a strategic asset in this information-exploding era of big data. There will be a demand for data fusion where there is information and data. Driven by the development of information technology, the digital construction of various fields, such as smart cities, intelligent transportation, and smart manufacturing, is steadily advancing. The digital construction in these fields will have a higher demand for data fusion algorithms. Thus, WiMi’s multi-view-based data fusion algorithm has extensive application prospects.
