基于人眼视点图的特征融合小目标检测算法

针对目前深度学习小目标检测算法在实际应用中存在的漏检率高、精度低等问题,提出了 一种基于人眼视点图的特征融合小目标检测算法.基于多类别单阶检测器(single shot multibox detection,SSD)算法通过不同扩张率的空洞卷积融合,在基础网络上获得具有类似人眼感受野的浅层特征层;对附加网络中的特征层进...

Feature fusion small target detection algorithm based on human eye view-point map

Aiming at the high missed detection rate and low accuracy of the current deep learning small target detection algorithm in practical applications, this paper proposes a feature fusion small target detection algorithm based on the human eye view-point map. Based on the single shot multibox detection (SSD) algorithm, through the convolution fusion of holes with different expansion rates, a shallow feature layer similar to the receptive field of the human eye is obtained on the basic network. The feature layer in the additional network performs information fusion, merges context information, adds position information and global semantic information, thereby improving the accuracy of small target detection. Validated by PASCAL VOC 2007 data set, the results show that the detection accuracy of this algorithm is improved by 3.7% compared with the traditional SSD algorithm, and the accuracy of the improved small target detection algorithm Bi-SSD is increased by 0.8%. It is verified that selecting a feature layer with more characterization ability is an effective method to improve the accuracy of small target detection.