Vehicle target detection method for remote sensing application scene

Abstract

The invention provides a vehicle detection method for a remote sensing application scene, and the method comprises the steps: making a diversified remote sensing image vehicle detection data set through a homography-based data enhancement method; determining candidate area positions and analogy based on a target detection model considering target area characteristics of a remote sensing image vehicle; improving the resolution of the low-resolution remote sensing image based on a super-resolution reconstruction model of the cyclic generative adversarial network; and completing super-resolutionreconstruction and vehicle detection tasks at the same time based on a synchronous super-division and target detection network model of a task driving thought. Compared with a traditional vehicle detection method, the method has the advantages of being high in efficiency, rich in depth feature semantic information and the like; compared with other vehicle detection algorithms based on deep learning, remote sensing image characteristics are considered, and the method has the advantages of being accurate in target positioning, good in generalization performance and the like. In addition, the multi-task learning model improves the vehicle detection precision of the low-resolution remote sensing image.

Description

technical field [0001] The present invention relates to the fields of computer vision and artificial intelligence, in particular to a vehicle target detection method for remote sensing application scenarios based on a deep convolutional network and a multi-task learning model. Taking into account the characteristics of remote sensing images, it can improve the resolution and Accurately locate vehicle targets. Background technique [0002] Optical remote sensing images can be captured with cameras mounted on UAVs, aircraft or satellites. The target detection task in the field of remote sensing is to determine whether an object of interest is contained in a remote sensing image, and to locate the object. Among them, vehicle detection plays an important role in rescue missions, traffic safety, military defense and other fields, and has important theoretical research significance and practical application value. [0003] Commonly used vehicle detection algorithms can be divide...

AI Technical Summary

Problems solved by technology

However, low / high-resolution paired images are required to train the super-resolution network, which requires high data sets and high costs.

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