Studies show that encoding technologies in H.264/AVC,including prediction and conversion,are essential technologies.However,these technologies are more complicated than the MPEG-4,which is a standard method and widely...Studies show that encoding technologies in H.264/AVC,including prediction and conversion,are essential technologies.However,these technologies are more complicated than the MPEG-4,which is a standard method and widely adopted worldwide.Therefore,the amount of calculation in H.264/AVC is significantly up-regulated compared to that of the MPEG-4.In the present study,it is intended to simplify the computational expenses in the international standard compression coding system H.264/AVC for moving images.Inter prediction refers to the most feasible compression technology,taking up to 60%of the entire encoding.In this regard,prediction error and motion vector information are proposed to simplify the computation of inter predictive coding technology.In the initial frame,motion compensation is performed in all target modes and then basic information is collected and analyzed.After the initial frame,motion compensation is performed only in the middle 8×8 modes,and the basic information amount shifts.In order to evaluate the effectiveness of the proposed method and assess the motion image compression coding,four types of motion images,defined by the international telecommunication union(ITU),are employed.Based on the obtained results,it is concluded that the developed method is capable of simplifying the calculation,while it is slightly affected by the inferior image quality and the amount of information.展开更多
When we use traditional computer vision Inspection technology to locate the vehicles,we find that the results were unsatisfactory,because of the existence of diversified scenes and uncertainty.So,we present a new meth...When we use traditional computer vision Inspection technology to locate the vehicles,we find that the results were unsatisfactory,because of the existence of diversified scenes and uncertainty.So,we present a new method based on improved SSD model.We adopt ResNet101 to enhance the feature extraction ability of algorithm model instead of the VGG16 used by the classic model.Meanwhile,the new method optimizes the loss function,such as the loss function of predicted offset,and makes the loss function drop more smoothly near zero points.In addition,the new method improves cross entropy loss function of category prediction,decreases the loss when the probability of positive prediction is high effectively,and increases the speed of training.In this paper,VOC2012 data set is used for experiment.The results show that this method improves average accuracy of detection and reduces the training time of the model.展开更多
基金supported by QingLan Project of Jiangsu Province and National Science Fund of China(Nos.61806088,61902160)was supported by Changzhou Science and Technology Support Plan(No.CE20185044).
文摘Studies show that encoding technologies in H.264/AVC,including prediction and conversion,are essential technologies.However,these technologies are more complicated than the MPEG-4,which is a standard method and widely adopted worldwide.Therefore,the amount of calculation in H.264/AVC is significantly up-regulated compared to that of the MPEG-4.In the present study,it is intended to simplify the computational expenses in the international standard compression coding system H.264/AVC for moving images.Inter prediction refers to the most feasible compression technology,taking up to 60%of the entire encoding.In this regard,prediction error and motion vector information are proposed to simplify the computation of inter predictive coding technology.In the initial frame,motion compensation is performed in all target modes and then basic information is collected and analyzed.After the initial frame,motion compensation is performed only in the middle 8×8 modes,and the basic information amount shifts.In order to evaluate the effectiveness of the proposed method and assess the motion image compression coding,four types of motion images,defined by the international telecommunication union(ITU),are employed.Based on the obtained results,it is concluded that the developed method is capable of simplifying the calculation,while it is slightly affected by the inferior image quality and the amount of information.
基金supported in part by National Natural Science Fund of China (61806088, 61902160)Qing Lan Project of Jiangsu Province and Natural Science Foundation of Jiangsu Province (BK20160293)Changzhou Science and Technology Support Plan (CE20185044).
文摘When we use traditional computer vision Inspection technology to locate the vehicles,we find that the results were unsatisfactory,because of the existence of diversified scenes and uncertainty.So,we present a new method based on improved SSD model.We adopt ResNet101 to enhance the feature extraction ability of algorithm model instead of the VGG16 used by the classic model.Meanwhile,the new method optimizes the loss function,such as the loss function of predicted offset,and makes the loss function drop more smoothly near zero points.In addition,the new method improves cross entropy loss function of category prediction,decreases the loss when the probability of positive prediction is high effectively,and increases the speed of training.In this paper,VOC2012 data set is used for experiment.The results show that this method improves average accuracy of detection and reduces the training time of the model.
