Building construction target detection method based on YOLO neural network

A neural network and target detection technology, which is applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as small scale, and achieve the effects of improving recognition accuracy, expanding search areas, and good recognition effects
CN110688955AInactive Publication Date: 2020-01-14XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
Publication Date
2020-01-14
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses a building construction target detection method based on a YOLO neural network. The method comprises the steps: 1, collecting original image data at a construction site, dividing the collected original image data into a test set and a training set, and carrying out the preprocessing of the training set; step 2, training a Darkne-53-based target recognition model of the YOLOneural network; 3, testing the target recognition model based on Darknet-53 by using the test set to obtain a test result; 4, analyzing a test result obtained in the step 3; and step 5, acquiring animage in the construction site, and detecting the building construction target in the acquired image by using a Darknet-53-based target recognition model. According to the method, the defect that theexisting YOLO algorithm cannot quickly and accurately identify the problems of deep target layer and small scale in the building construction site image is solved.
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Description

technical field

[0001] The invention relates to the field of deep learning target detection, in particular to a method for detecting building construction targets based on a YOLO neural network. Background technique

[0002] With the rapid development of my country's construction industry, prefabricated buildings have gradually begun to play an increasingly important role under the trend of increasingly strict technical and construction period requirements in the construction industry. The target detection of prefabricated buildings will have very important research significance.

[0003] As a part of computer vision, target detection technology aims to quickly locate and classify targets in images. The target detection of prefabricated building construction is to locate and classify the building construction to be assembled on the construction site. The existing YOLO algorithm can achieve high recognition efficiency when the image structure is clear, the target size is app...

Claims

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