Beijing, China – WiMi Hologram Cloud Inc., a global hologram augmented reality technology provider, has announced the development of a 3D target recognition algorithm system based on deep learning. Deep learning can simulate the human brain’s visual system with its characteristics of passing from concrete to abstraction and multiple layers.
By building multilayer neural networks, the system extracts and abstracts feature from the original information layer by layer, making classification, recognition, and prediction easier and more accurate. In recent years, deep learning has played an increasingly important role in artificial intelligence fields, such as image and natural language processing, with social value and economic benefits.
WiMi’s 3D target recognition algorithm is based on a large amount of training data and learns features layer by layer from a large amount of data to fully extract the features of 3D target data. To a large extent, the algorithm can retain the characteristics of 3D target image quality, thus fully expressing the high-level semantic information in the image, greatly enhancing the detection accuracy and improving the effectiveness. At the same time, the algorithm improves its applicability in multiple types of complex tasks and performs better in complex tasks. The algorithm can thoroughly learn the features in the sample data. And the trained model can detect and recognise various types of targets, speeding up the 3D target detection and recognition and improving the accuracy rate.
With the progress of 3D data acquisition technology, the enhancement of computing power, the development of deep learning technology, and the increase in application demand, the research and application of 3D vision technology have received more and more attention. 3D target detection and recognition is the crucial technology and the basis for machines to understand and interact with the world. WiMi will continue to expand its deep learning-based 3D target recognition algorithm in the field of application.
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