2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT)最新文献

筛选

英文中文

Towards Federated Learning Based Contraband Detection Within Airport Baggage X-Rays 基于联邦学习的机场行李x射线违禁品检测

2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) Pub Date : 2022-12-15 DOI: 10.1109/ICMLANT56191.2022.9996472

Sai Puppala, Ismail Hossain, Sajedul Talukder

{"title":"Towards Federated Learning Based Contraband Detection Within Airport Baggage X-Rays","authors":"Sai Puppala, Ismail Hossain, Sajedul Talukder","doi":"10.1109/ICMLANT56191.2022.9996472","DOIUrl":"https://doi.org/10.1109/ICMLANT56191.2022.9996472","url":null,"abstract":"To maintain border and transportation security against a variety of threat profiles, it is essential to find contraband in airport baggage X-rays. Security inspectors have a tougher time avoiding misdetection due to a lack of support staff and a stressful workplace. Although machine learning models can detect contraband automatically, most of the models used in this process train the data in a centralized learning (CL) way, posing possible security and privacy concerns. To address this, we propose a Federated learning (FL)-based architecture to detect contraband in x-ray baggage security images while maintaining user privacy. Our model is trained and evaluated using the most recent state-of-the-art YOLOv7, SSD, and Faster R-CNN algorithms, paving the door for large-scale automatic detection of contraband in airports across the globe through collaboration. We achieve a global accuracy of 90.1%, 86.4%, and 66.7% with Faster R-CNN, SSD, and YOLOv7 algorithms respectively using the PIDray dataset. Our experiment reveals the challenges and potential of utilizing FL to detect contraband in airport luggage X-rays, even though the performance is comparable with the benchmark performance of non-FL algorithms.","PeriodicalId":224526,"journal":{"name":"2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125692560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

MQTT based Push to talk application for Retail Stores 基于MQTT的零售商店推送对话应用程序

2022 IEEE International Conference on Machine Learning and Applied Network Technologies (ICMLANT) Pub Date : 2022-12-15 DOI: 10.1109/ICMLANT56191.2022.9996492

Sandeep Shekhawat

引用次数: 0

首页上一页