Remote sensing image target detection method based on deep evolution pruning convolutional network

A target detection and depth convolution technology, applied in the field of image processing, can solve the problems affecting the computational complexity and computational speed of the model, difficult optical remote sensing image detection, and overall accuracy loss, so as to overcome the loss of model operation speed and reduce model parameters. amount, the effect of accelerating the convergence speed
CN110532859AActive Publication Date: 2019-12-03XIDIAN UNIV
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
XIDIAN UNIV
Publication Date
2019-12-03

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Abstract

The invention discloses a remote sensing image target detection method based on a deep evolution pruning convolutional network. The problem that the detection speed and the detection precision are notglobally and effectively optimized at the same time in existing remote sensing image target detection is solved. The method comprises the specific steps of processing a data set; constructing a deepconvolution feature extraction subnet; constructing a full convolution FCN detection subnet; constructing and training a deep convolution target detection network; constructing and training a target detection network based on a deep evolution pruning convolutional network; performing target detection on the test data set by using the trained model; and outputting test results. According to the method, a reverse residual structure is constructed by using depth separable convolution, so that the model parameter quantity is greatly reduced while the detection precision is high; the target detection network is combined with evolutionary pruning to realize global acceleration. The method greatly reduces the calculation amount, remarkably improves the target detection speed, is high in detectionprecision, and is used for the quick and accurate detection of small targets in a remote sensing image, such as an airplane and a ship.
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Description

technical field

[0001] The invention belongs to the technical field of image processing, and further relates to remote sensing image target detection, specifically a remote sensing image target detection method based on deep evolutionary pruning convolutional network, which can be applied to aircrafts and ships in different areas in remote sensing images ground object detection. Background technique

[0002] Target detection technology is one of the core issues in the field of computer vision. Remote sensing image target detection refers to the use of images captured by remote sensing satellites as data sources, and the use of image processing technology to locate and classify objects of interest in the images. Remote sensing image target detection, as a key technology in the application of remote sensing images, can capture attack targets and provide accurate location and category information in high-tech military confrontation. It has a significant impact on the military f...

Claims

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