The invention relates to a method and a
system for realizing
remote sensing image target detection based on a deep neural network, and a storage medium thereof, so as to realize detection of horizontal and rotary arrangement targets of a
remote sensing image. According to the method, an
anchor point box generation module is designed, an
anchor point box is generated in a self-adaptive mode throughfeature information of different positions, and the influence of the difference of preset
anchor point boxes on detection precision is reduced; aiming at the characteristic that more small targets exist in a
remote sensing image, an improved feature
pyramid structure is provided, and deep and shallow layer feature information is fused by adopting a transposed
convolution method; aiming at difficulties such as complex background of a remote sensing image, a
receptive field expanding module is adopted to extract more characteristic information, and the detection precision of a
small target under a complex background is improved; a SmoothLn function is adopted as regression loss, so that the
algorithm performance is further improved; for a rotation arrangement target, regression of an anglefactor is introduced to realize rotation frame detection. In addition, in order to facilitate the use of a user, the remote sensing image target detection
system designed by the invention has the functions of horizontal frame and rotary frame detection and result statistics.