In order to solve difficult detection of far and hard objects due to the sparseness and insufficient semantic information of LiDAR point cloud,a 3D object detection network with multi-modal data adaptive fusion is pro...In order to solve difficult detection of far and hard objects due to the sparseness and insufficient semantic information of LiDAR point cloud,a 3D object detection network with multi-modal data adaptive fusion is proposed,which makes use of multi-neighborhood information of voxel and image information.Firstly,design an improved ResNet that maintains the structure information of far and hard objects in low-resolution feature maps,which is more suitable for detection task.Meanwhile,semantema of each image feature map is enhanced by semantic information from all subsequent feature maps.Secondly,extract multi-neighborhood context information with different receptive field sizes to make up for the defect of sparseness of point cloud which improves the ability of voxel features to represent the spatial structure and semantic information of objects.Finally,propose a multi-modal feature adaptive fusion strategy which uses learnable weights to express the contribution of different modal features to the detection task,and voxel attention further enhances the fused feature expression of effective target objects.The experimental results on the KITTI benchmark show that this method outperforms VoxelNet with remarkable margins,i.e.increasing the AP by 8.78%and 5.49%on medium and hard difficulty levels.Meanwhile,our method achieves greater detection performance compared with many mainstream multi-modal methods,i.e.outperforming the AP by 1%compared with that of MVX-Net on medium and hard difficulty levels.展开更多
Objective To explore the relationship among myocardial infarction (MI) , promoter regionpolymorphism of FVII gene and FVII activity in a Chinese population. Methods Denaturing gradient gel electro-phoresis technique w...Objective To explore the relationship among myocardial infarction (MI) , promoter regionpolymorphism of FVII gene and FVII activity in a Chinese population. Methods Denaturing gradient gel electro-phoresis technique was used to study promoter region polymorphism of FVII gene, and plasma FVII activity (FVIIC) was examined by one stage clotting assay in 74 cases with MI as well as 123 normal controls. Results An insertion/deletion polymorphism of 10bp was found in the promoter region. Plasma FVII activity was significantly higher in the myocardial infarction (P <0. 05). Conclusion Elevated FVII activity may be a risk factor for myocardial infarction. There is no correlation found between the insertion/deletion polymorphism of FVII gene promoter region and myocardial infarction in a Chinese population (74 MI cases and 123 normal controls).展开更多
基金National Youth Natural Science Foundation of China(No.61806006)Innovation Program for Graduate of Jiangsu Province(No.KYLX160-781)Jiangsu University Superior Discipline Construction Project。
文摘In order to solve difficult detection of far and hard objects due to the sparseness and insufficient semantic information of LiDAR point cloud,a 3D object detection network with multi-modal data adaptive fusion is proposed,which makes use of multi-neighborhood information of voxel and image information.Firstly,design an improved ResNet that maintains the structure information of far and hard objects in low-resolution feature maps,which is more suitable for detection task.Meanwhile,semantema of each image feature map is enhanced by semantic information from all subsequent feature maps.Secondly,extract multi-neighborhood context information with different receptive field sizes to make up for the defect of sparseness of point cloud which improves the ability of voxel features to represent the spatial structure and semantic information of objects.Finally,propose a multi-modal feature adaptive fusion strategy which uses learnable weights to express the contribution of different modal features to the detection task,and voxel attention further enhances the fused feature expression of effective target objects.The experimental results on the KITTI benchmark show that this method outperforms VoxelNet with remarkable margins,i.e.increasing the AP by 8.78%and 5.49%on medium and hard difficulty levels.Meanwhile,our method achieves greater detection performance compared with many mainstream multi-modal methods,i.e.outperforming the AP by 1%compared with that of MVX-Net on medium and hard difficulty levels.
基金Supported by the Scientific and Technological Committee of Shanghai (974119003)
文摘Objective To explore the relationship among myocardial infarction (MI) , promoter regionpolymorphism of FVII gene and FVII activity in a Chinese population. Methods Denaturing gradient gel electro-phoresis technique was used to study promoter region polymorphism of FVII gene, and plasma FVII activity (FVIIC) was examined by one stage clotting assay in 74 cases with MI as well as 123 normal controls. Results An insertion/deletion polymorphism of 10bp was found in the promoter region. Plasma FVII activity was significantly higher in the myocardial infarction (P <0. 05). Conclusion Elevated FVII activity may be a risk factor for myocardial infarction. There is no correlation found between the insertion/deletion polymorphism of FVII gene promoter region and myocardial infarction in a Chinese population (74 MI cases and 123 normal controls).
