Aircraft Recognition from Remote Sensing Images Based on Machine Vision
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초록
Due to the poor evaluation indexes such as detection accuracy and recall rate when Yolov3 network detects aircraft in remote sensing images, in this paper, we propose a remote sensing image aircraft detection method based on machine vision. In order to improve the target detection effect, the Inception module was introducedinto the Yolov3 network structure, and then the data set was cluster analyzed using the kmeans algorithm. In order to obtain the best aircraft detection model, on the basis of our proposed method, we adjusted the network parameters in the pretraining model and improved the resolution of the input image. Finally, our methodadopted multiscale training model. In this paper, we used remote sensing aircraft dataset of RSODDataset to do experiments, and finally proved that our method improved some evaluation indicators. The experiment of this paper proves that our method also has good detection and recognition ability in other ground objects.
Abstract
Due to the poor evaluation indexes such as detection accuracy and recall rate when Yolov3 network detects aircraft in remote sensing images, in this paper, we propose a remote sensing image aircraft detection method based on machine vision. In order to improve the target detection effect, the Inception module was introducedinto the Yolov3 network structure, and then the data set was cluster analyzed using the kmeans algorithm. In order to obtain the best aircraft detection model, on the basis of our proposed method, we adjusted the network parameters in the pretraining model and improved the resolution of the input image. Finally, our methodadopted multiscale training model. In this paper, we used remote sensing aircraft dataset of RSODDataset to do experiments, and finally proved that our method improved some evaluation indicators. The experiment of this paper proves that our method also has good detection and recognition ability in other ground objects.
참고문헌 (12)
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