Cascade two wheeler helmet detection algorithm using sparse convolution
With the rise of express delivery industry,the number of two wheeler represented by electric ve-hicles and motorcycles has increased sharply,and traffic accidents occur frequently.Due to the large num-ber of two wheeled vehicles,the management will consume a lot of police force,and this study can greatly release the police force.To solve the time-consuming problem of high-resolution feature layer calculation in the object detection algorithm,this paper proposes a Cascade two wheeler helmet detection algorithm using sparse convolution,which improves the speed by 33.3%.In addition,for the misjudgment of pedestrians and cyclists without helmets,multi-scale dilated convolution is adopted.By introducing context informa-tion,such misjudgment can be effectively reduced and the accuracy can be improved by 2.2%.Finally,we annotate and open source TWHD dataset to verify the performance of the algorithm.
deep learningtwo wheeler helmet detectionsmall object detectionsparse convolutionmulti-scale dilated convolution
万方数据
维普
