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Friday, February 03, 2023 5:18:12 AM
Source
https://www.newstrail.com/wimi-develops-the-3d-object-recognition-algorithm-system-based-on-deep-learning/
February 1, 2023
Target recognition has always been an essential technology in computer vision. The process of target recognition can be understood as visual algorithms giving computers the ability of visual recognition similar to that of humans so that they can recognize the target category through the image information obtained by sensors and obtain the geometric shape, position, and posture of the target in the imaging environment. Object recognition involves many subjects, such as pattern recognition, computer science, image processing, and machine vision. Three-dimensional object recognition is one of the key technologies to realize machine perception and understanding of a three-dimensional environment. It has many application demands in intelligent transportation systems and control, biomedical equipment, industrial automation, aerospace navigation and remote sensing, and other prominent fields. It is also widely used in indoor robot visual recognition systems to realize understanding and interaction of complex indoor scenes.
With the rapid development of 3D sensors and other hardware equipment, the cost of 3D data acquisition and acquisition is getting lower and lower compared to the past, and the technical route of 3D target recognition is gradually changing from the method of combining 3D features and classification algorithms such as support vector machine to the 3D target recognition method based on deep learning. For 3D target recognition tasks, It is essential to design a fast recognition algorithm with a high recognition rate.
WiMi Hologram Cloud, Inc. (NASDAQ: WIMI) has developed a 3D object recognition algorithm system based on deep learning. Deep learning simulates the human visual system, characterized by multi-layer transmission from concrete to abstract. By constructing a multi-layer neural network, feature extraction and abstraction of original information are carried out 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 processing and natural language processing, with substantial social value and economic benefits.
Based on a large amount of training data, WiMi’s 3D target recognition algorithm learns features layer by layer from a large amount of data, fully extracts the features of 3D target data, preserves the features of 3D target image quality to a large extent, and fully expresses the high-level semantic information in the image, greatly improving the detection accuracy. The effect of the 3D object detection and recognition algorithm is enhanced. At the same time, it improves the applicability in multiple types of complex tasks, performs well in complex tasks, can thoroughly learn the features in the sample data, and trained model can detect and recognize all kinds of targets, which not only speeds up the speed of three-dimensional target detection and recognition but also improves the accuracy.
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. Three-dimensional object detection and recognition are crucial for three-dimensional scene understanding and the basis for machines to understand and interact with the world. It has broad application prospects in such fields as automatic driving, intelligent robots, ARVR, remote sensing mapping, and biomedicine. WiMi will also continue to expand the application field of three-dimensional object recognition algorithms based on deep learning.
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