【摘要】 提出了一种用于空中红外目标检测的增强单发多框检测器(SSD)方法。分析了感受野与特征图层数的关系,同时采用池化和转置卷积操作的特征图双向融合机制,从整体上增强了特征的表达能力。通过引入浅层特征图的语义增强分支,并在高分辨率特征图上增加预测框,可提升小尺寸目标的定位精度。在VOC2007小目标和空中红外目标数据集上进行了对比测试,平均精度分别提高了7.1%和8.7%,此时检测速度略有下降。结果表明,增强SSD可在空中红外目标检测中获得较好的性能。更多还原

【Abstract】 A method for enhancement of a single shot multibox detector(SSD) for aerial infrared target detection is proposed. Herein, the relationship between the sensing field and number of feature layers is analyzed, and a bidirectional feature map fusion mechanism that uses both pooling and deconvolution operations is proposed to enhance the feature expression ability. The semantic enhancement branch of the shallow feature map is introduced and the prediction boxes on the high-resolution feature map are increased, so that the positing accuracy of small-size targets is improved. Comparative experiments on the VOC2007 small object dataset and an aerial infrared target dataset reveal that the mean average precisions increase by 7.1% and 8.7%, respectively, accompanied by a slight decrease in detection speed. The results demonstrate that SSD enhancements can achieve good performance in aerial infrared target detection.更多还原