A Fast Target Detection Method in Remote Sensing Image Based on Rotation Anchor Point Clustering
A remote sensing image and detection method technology, which is applied in the field of remote sensing image target detection, can solve the problems of cumbersome parameter adjustment in the training process, poor anchor point pertinence, and large anchor point redundancy, so as to reduce the number of anchor points and improve detection Accuracy and detection speed, the effect of easy algorithm
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[0042] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.
[0043] The present invention first finds a suitable rotation anchor point through an algorithm based on k-means clustering, and then uses a two-stage detection algorithm to detect a specific target to improve the slow detection speed of remote sensing image targets. as follows:
[0044] (1) After preprocessing the input image, the feature information of the image is extracted by the deep convolutional neural network as the backbone network, and output to the next link as the feature map;
[0045] (2) Use the k-means clustering algorithm to cluster the labeled frame data in the training set image, and use the scale, width and height as prior information on the feature map to count the k most representative anchor points, It performs rotation processing to obtain the rotation anchor point that is most likely to cover the target;
[0046] (3) Perf...
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