Research on tiny ship detection algorithm based on sample reconstruction
Aiming at the problems of small ship target scale,uneven scene distribution,small proportion of target size relative to sample size and poor generalization performance of deep learning model for small targets in remote sensing images,a sample reconstruction method is proposed.Firstly,the ship target is cut according to its smallest circumscribed rectangle,and then a standard size sample is synthesized in various ways.Through sample reconstruction,the proportion of targets in the sample can be increased,and the problem of uneven distribution of targets in different scenarios can be solved.The experiment found that the model trained by the sample reconstruction method has improved the detection ability of small targets.Combined with adding a small target detection layer to the network,the results show that the Average Precision(AP)of the model on the test sample arising from 0.502 to 0.674,verifying the effectiveness of the method.
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