In the study of oriented bounding boxes(OBB)object detection in high-resolution remote sensing images,the problem of missed and wrong detection of small targets occurs because the targets are too small and have differ...In the study of oriented bounding boxes(OBB)object detection in high-resolution remote sensing images,the problem of missed and wrong detection of small targets occurs because the targets are too small and have different orientations.Existing OBB object detection for remote sensing images,although making good progress,mainly focuses on directional modeling,while less consideration is given to the size of the object as well as the problem of missed detection.In this study,a method based on improved YOLOv8 was proposed for detecting oriented objects in remote sensing images,which can improve the detection precision of oriented objects in remote sensing images.Firstly,the ResCBAMG module was innovatively designed,which could better extract channel and spatial correlation information.Secondly,the innovative top-down feature fusion layer network structure was proposed in conjunction with the Efficient Channel Attention(ECA)attention module,which helped to capture inter-local cross-channel interaction information appropriately.Finally,we introduced an innovative ResCBAMG module between the different C2f modules and detection heads of the bottom-up feature fusion layer.This innovative structure helped the model to better focus on the target area.The precision and robustness of oriented target detection were also improved.Experimental results on the DOTA-v1.5 dataset showed that the detection Precision,mAP@0.5,and mAP@0.5:0.95 metrics of the improved model are better compared to the original model.This improvement is effective in detecting small targets and complex scenes.展开更多
索尼董事长兼首席执行官霍华德·斯丁格（Howard Stringer）在“2009 International CES”上展示了眼镜式显示器。虽然尼康也发布了同样的视频眼镜，但后者只是单侧有视频元件。与其不同，素尼产品在两侧都有视频元件。戴了这种眼...索尼董事长兼首席执行官霍华德·斯丁格（Howard Stringer）在“2009 International CES”上展示了眼镜式显示器。虽然尼康也发布了同样的视频眼镜，但后者只是单侧有视频元件。与其不同，素尼产品在两侧都有视频元件。戴了这种眼镜。前方看到的景色依然如故，但中部的略下方显示着一个图像框。戴这种眼镜还可享受欣赏3D影像的乐趣。展开更多
文摘In the study of oriented bounding boxes(OBB)object detection in high-resolution remote sensing images,the problem of missed and wrong detection of small targets occurs because the targets are too small and have different orientations.Existing OBB object detection for remote sensing images,although making good progress,mainly focuses on directional modeling,while less consideration is given to the size of the object as well as the problem of missed detection.In this study,a method based on improved YOLOv8 was proposed for detecting oriented objects in remote sensing images,which can improve the detection precision of oriented objects in remote sensing images.Firstly,the ResCBAMG module was innovatively designed,which could better extract channel and spatial correlation information.Secondly,the innovative top-down feature fusion layer network structure was proposed in conjunction with the Efficient Channel Attention(ECA)attention module,which helped to capture inter-local cross-channel interaction information appropriately.Finally,we introduced an innovative ResCBAMG module between the different C2f modules and detection heads of the bottom-up feature fusion layer.This innovative structure helped the model to better focus on the target area.The precision and robustness of oriented target detection were also improved.Experimental results on the DOTA-v1.5 dataset showed that the detection Precision,mAP@0.5,and mAP@0.5:0.95 metrics of the improved model are better compared to the original model.This improvement is effective in detecting small targets and complex scenes.
文摘索尼董事长兼首席执行官霍华德·斯丁格（Howard Stringer）在“2009 International CES”上展示了眼镜式显示器。虽然尼康也发布了同样的视频眼镜，但后者只是单侧有视频元件。与其不同，素尼产品在两侧都有视频元件。戴了这种眼镜。前方看到的景色依然如故，但中部的略下方显示着一个图像框。戴这种眼镜还可享受欣赏3D影像的乐趣。
