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作 者:王守军 汪新凯 王炜 王月恒 陈树雷 林枫 王晶 李志国 WANG Shou-Jun;WANG Xin-Kai;WANG Wei;WANG Yue-Heng;CHEN Shu-Lei;LIN Feng;WANG Jing;LI Zhi-Guo(Chinese Academy of Customs Administration,Qinhuangdao 066004;Lianyungang Customs,Lianyungang 222000;Nanjing Customs,Nanjing 210001;Beijing Xinsheng Hengyuan Technology Co.,Ltd.,Beijing 100080)
机构地区:[1]中国海关管理干部学院,秦皇岛066004 [2]连云港海关,连云港222000 [3]南京海关,南京210001 [4]北京鑫晟恒远科技有限公司,北京100080
出 处:《中国口岸科学技术》2024年第12期83-89,共7页China Port Science and Technology
基 金:海关总署科研项目(2024HK197)。
摘 要:本文在分析海关旅客通关流程和信息化建设现状,以及目前海关旅检“人”“物”关联、风险拦截、查验处置等探索和实施情况的基础上,提出了应用卷积神经网络(Convolutional Neural Networks,CNN)建立AI信息链,融合应用态势感知、智能识别、数据融合、风险预警和传输处置等技术,通过深度学习和大数据分析,建立对旅客信息智能关联和风险评估的新方法和思路。同时,设计了完整的“人”“物”关联、布控拦截、查验监督体系并进行了实效验证,有助于实现“人”“物”准确关联及拦截,做到“无感通关、智能监管、无事不扰、无处不在”。Based on the analysis of the business model and the current status of information technology in customs passenger clearance,as well as the exploration and implementation of the association between“person”and“item”in customs travel inspection,risk interception,inspection and disposal,this article proposes the application of convolutional neural networks(CNN)to establish an AI information chain.This approach integrates technologies such as situational awareness,intelligent recognition,data fusion,risk warning and transmission disposal.Through deep learning and big data analysis,a new method is developed for the intelligent association and risk assessment of passenger information.Additionally,this study have designed a complete system for the association of“person”and“item”,control interception,inspection supervision,and conducted practical verification,which has helped achieved accurate interaction and interception of“person”and“item”,resolved the bottleneck that restricts the development of intelligent travel inspection,and achieved“unconscious clearance,automatic(intelligent)supervision,no disturbance,and ubiquitous monitoring”.
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