Image target detection method and device based on dynamic label distribution
A technology of target detection and distribution, which is applied in the field of computer vision to achieve the effect of improving performance and detection accuracy
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Embodiment 1
[0044] like figure 1 Shown is an image target detection method based on dynamic label allocation disclosed in this embodiment, which is suitable for airport aircraft detection or other image target detection in satellite images. The method specifically includes the following steps:
[0045] Step 1, preprocessing the images marked with targets to be detected to obtain training images and verification images, and collecting the training images into a training image set, and collecting the verification images into a verification image set;
[0046] Step 2, construct an end-to-end target detection model, and improve the end-to-end target detection model, including normalization improvement and improvement of label assignment method based on regression state;
[0047] Step 3, iteratively train the improved end-to-end target detection model through the training image set, and use the verification image set to verify the accuracy of the end-to-end target detection model in each round...
Embodiment 2
[0067] like image 3Shown is an image object detection device based on dynamic label allocation disclosed in this embodiment, which is suitable for airport aircraft detection or other image object detection in satellite images. The image target detection device includes an image processing module, a model building module, a model training module and a target detection module. Wherein, the image processing module is used to preprocess the images marked with the target to be detected to obtain training images and verification images, and collect the training images into the training image set, and collect the verification images into the verification image set; model construction The module is used to improve the end-to-end target detection model based on the SparseRCNN network, and construct the improved end-to-end target detection model, wherein the improvement of the end-to-end target detection model includes normalization improvement and regression state-based dynamic The l...
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