2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2)最新文献_第7页

Cost Effective Welding System by using AR3 Robot 基于AR3机器人的低成本焊接系统

2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2) Pub Date : 2022-05-24 DOI: 10.1109/ICoDT255437.2022.9787444

Seemal Asif

引用次数: 0

Baggage Threat Detection Under Extreme Class Imbalance 极端舱位不平衡下的行李威胁检测

2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2) Pub Date : 2022-05-24 DOI: 10.1109/ICoDT255437.2022.9787472

A. Ahmed, D. Velayudhan, Taimur Hassan, Bilal Hassan, J. Dias, N. Werghi

{"title":"Baggage Threat Detection Under Extreme Class Imbalance","authors":"A. Ahmed, D. Velayudhan, Taimur Hassan, Bilal Hassan, J. Dias, N. Werghi","doi":"10.1109/ICoDT255437.2022.9787472","DOIUrl":"https://doi.org/10.1109/ICoDT255437.2022.9787472","url":null,"abstract":"Automatic detection of prohibited items is a critical but difficult task during aviation security. Manual detection of such items is a time-consuming process that is also limited by the examination capacity of the security inspector. To overcome these constraints, several researchers have proposed deep learning solutions to identify contraband data contained within baggage X-ray imagery. However, when trained on the imbalanced data that is frequently encountered in real-world aviation screening, the performance of these models suffers significantly. Towards this end, this paper proposes the coupling of various imbalanced learning strategies that can be used to augment traditional threat detection models and enable them to effectively learn the extremely imbalanced distribution of normal and threat object categories. The proposed approach is validated on three public datasets, namely SIXray, OPIXray, and COMPASS-XP, where it achieved the performance improvement of 9.52%, 11.32%, and 10.98%, respectively, on all three datasets in terms of mean intersection-over-union as compared to the state-of-the-art threat detection frameworks.","PeriodicalId":291030,"journal":{"name":"2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132933632","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: 3

Programmable Broad Learning System to Detect Concealed and Imbalanced Baggage Threats 可编程的广泛学习系统，以检测隐藏和不平衡的行李威胁

2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2) Pub Date : 2022-05-24 DOI: 10.1109/ICoDT255437.2022.9787420

Muhammad Shafay, Taimur Hassan, A. Ahmed, D. Velayudhan, J. Dias, N. Werghi

{"title":"Programmable Broad Learning System to Detect Concealed and Imbalanced Baggage Threats","authors":"Muhammad Shafay, Taimur Hassan, A. Ahmed, D. Velayudhan, J. Dias, N. Werghi","doi":"10.1109/ICoDT255437.2022.9787420","DOIUrl":"https://doi.org/10.1109/ICoDT255437.2022.9787420","url":null,"abstract":"Manual screening of baggage at airports, shopping malls, and shipments to identify potentially dangerous items is a time-consuming process that requires the unwavering efforts of a human observer. Numerous researchers have addressed this issue by developing autonomous threat detection systems. However, the performance of these systems is still vulnerable to high occlusion and unbalanced contraband data. In this paper, we present a novel programmable CNN-driven broad learning system (BLS) that automatically adapts its design specifications to effectively recognize the concealed and imbalanced contraband data depicted within the baggage X-ray scans. First, the input scan is passed to the CNN backbone to extract distinct latent features. These features are then passed to the BLS model, which determines whether the scan contains potentially dangerous items or not. Additionally, the BLS’s architecture (within the proposed framework) is programmed in such a way that no human effort is required to optimize it for producing the best threat detection performance. This novel design adaptation is performed via heuristics and greedy searches that quantify the importance of each edge fusing the adjacent node pairs to optimize the network’s overall performance. The proposed system is thoroughly tested on three datasets, namely GDXray, SIXray, and COMPASS-XP, on which it leads the state-of-the-art by 2.94%, 19.33%, and 13.38%, respectively, in terms of F1 score.","PeriodicalId":291030,"journal":{"name":"2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2)","volume":"35 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133077463","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: 4

3D printing of nanocellulose structures infused Epofix resin with improved mechanical properties 纳米纤维素结构的3D打印注入环氧树脂改善机械性能

2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2) Pub Date : 2022-05-24 DOI: 10.1109/ICoDT255437.2022.9787423

M. Latif, Yangxiaozhe Jiang, B. Kumar, Jaehwan Kim

引用次数: 0

An enhanced agile-V model for system engineering in complex medical device development 一种用于复杂医疗器械开发系统工程的增强敏捷- v模型

2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2) Pub Date : 2022-05-24 DOI: 10.1109/ICoDT255437.2022.9787446

A. A. Khan, M. Akram, A. A. Salam, Wasi Haider Butt

引用次数: 1