Cigarette end detection based on EfficientDet

Abstract

In the process of building a harmonious society in China, smoking in public places is difficult to curb. However, with the continuous development of computer vision, object detection algorithm plays a key role in the above video detection scene. However, if the detection process is not real-time, it can not be applied to smoking scenes in public places, giving people timely judgment. After analyzing a variety of target detection algorithms, this paper considers that EfficientDet can achieve high efficiency under a wide range of resource constraints, and can easily carry out multi-scale feature fusion, so that it has high speed and accuracy in the process of target detection. In this paper, Efficientnet is used as the backbone feature extraction network, and a set of fixed scaling coEfficients are used to scale the depth, width and resolution of the network for preliminary feature extraction, so as to obtain three effective feature layers. Then, in order to improve the prediction level and enhance the feature extraction, the three effective feature layers are transferred to bifpn with cross-scale connection optimization The prediction results can be used as the evaluation results of the model. The evaluation results show that EfficientDet has high mAP.