WiMi Hologram Cloud has announced the development of a 3D-CNN hologram

 

WiMi Hologram Cloud has announced the development of a 3D-CNN hologram classification algorithm that utilizes deep learning and convolutional neural networks for accurate and fast classification of 3D objects in holograms.  The 3D-CNN (Convolutional Neural Network) algorithm extracts feature information and optimizes it layer by layer, enabling automatic recognition and classification of holograms.  WiMi's 3D-CNN-based hologram classification technology effectively handles the 3D and wavefront information of holograms and achieves higher accuracy classification by utilizing deep neural networks. The algorithm finds applications in various fields, including autonomous driving, medical image diagnosis, intelligent security, and virtual reality. In autonomous driving, hologram classification aids in identifying vehicles, pedestrians, and traffic lights for automated driving decisions and safety detection. Medical image diagnosis benefits from hologram classification by enabling fast and accurate diagnoses for improved efficiency. VR experiences are enriched with object recognition in the virtual world using hologram classification.